Hi and welcome to data futurology the podcast for that enthusiasts data scientist and upcoming data science leaders to learn the skills required to take your career to the next level. We do this by learning directly from current leaders and Executives influencing and making a better industry today. My name is Felipe Flores. I am your host and thank you so much for listening. If you are a first-time listener welcome. I hope that you check out some of the other episodes. And enjoy them as well if you have been listening for a while then thank you. Thank you so much. And I hope that you enjoyed today's episode 2 today. We'll be speaking with you Velma ROM and what can I say about your well, I really admire. The guy he is a formidable presence in the data science Industry in Melbourne, Australia until recently he was head of data science at I select and they're built an extraordinary team of fantastic data scientists doing excellent work. And he has also found time to help run that assigns Melbourne meet up and also the our user group in Melbourne, really really amazing work you are has recently moved to work in a start-up is very secret at the moment, but he tells us about the rest of his journey and how he got where he is. It's a really great episode and I hope you enjoyed hi, this is sleeping today. I'm sitting with your well, how are you doing? Mate? Good. Thanks. How are you? Great. So great. Thanks so much for making the time. Thank you for being on the show. So I'm very excited to have you on the show today. Thanks for having me. All right, very excited. So tell me how did you originally get into the data space? What was it that helped you in and and brought you into the area, but both my parents are statisticians. I had it at home. There was no choice. I got to UNI and studying stats in computer science. And because I had them to help me out of it quickly just fell in love with it. Just what you can do with data and just wanting to get better at it and know what the tools are and solve real problems pretty early age. I was pretty clear on it. So SEO growing up. Did your parents show you examples of where to apply statistics. So how did they get you excited about the field as you were growing up. Do you have any memories from that? I think was more was I started going to Union? I got to understand because they are condemned Excel got to understand the world of it and seeing what we were able to achieve and the kind of areas are the well because they've done be of Consulting kind of areas like health education where they've been able to make a difference by using statistics and showing actionable insights. So yeah. Yeah, definitely piqued my interest. I don't know them explicitly remember as a kid. Yeah, but I'm sure things happening in and I was hearing things. Yeah influenced some seeds there. Yeah, but that's great to see the impact of stats in different Industries while I CUNY while studying at seeing what it could be. Definitely it's not new. There's a lot of focus on right now, but this stuff is but we're doing it for a long time and good idea to do a double with computer science. Yeah. How did you come to that decision? So there's also actually Background in the family as well. So that Drew my interest because I started programming when I was six seven. I loved it. So the combination is really what got me excited. So the being able to build stuff by using programming skills and making good use of data to find interesting inciting actionable insights combination of the two is for me was the explosive combination again, it was very clear to me that I wanted to be doing both and luckily, you know, there was back then already the word degrees that could offer them. Of course, they want to call data science, but it's Lucky joint computer science and statistics. It was I love it. So good. What did you program when you were initially was Pascal very very early days moved in to see so University yossi. And as a kid, what did you build on Pascal? I will see some gains the spaceship games we get to shoot the spaceships going across the screen. That's how I learned. Yeah. My dad just bought me a PC and a book that taught you Pascal and it's part of the learning the exercises were to design game to build this game. So as a kid, Of course he wanted to get to get to the end so you can actually do it. So I was very motivated. It's kind of a got me started and I realize I was very passionate about it. That's so crazy. Oh, well Donna especially to do the graphic side. I think there would have been yeah. Yeah, it's pretty basic but still yeah. Yeah, I know dis me graphic stuff. That's great. So then you study statistics and computer science and after the bachelor like what happen next? So at the end of my bachelor, there are a couple of units on neural networks and decision trees. That was my first exposure to machine learning and AI or raising and I just loved it so much again just fell in love. So I definitely to do a PhD so I chose to do a PhD in AI. Yeah, that's really all I was looking for and preferably overseas and I stumbled on to the University of Edinburgh a I was kind of born so they still had a department of AI back then and there was a someone was looking for a PhD summer to do a PhD in robotics as like, yeah, that could be challenging. Didn't have any interest in robotics up to the end but knowing how much data a robot senses with all his senses and how messy that data. Is that Drew me to going there because I knew it'd be a challenge some real messy real world data to play with and you do some AI That's why I did it or how did you end up picking that University and that supervisor or there was an opportunity. That's yeah. There was an opening so like that in bright heard about it. I was visiting there my parents were living in the UK the time as well, so it's kind of nice too because with him again, it was clear that any Brad was one of the leaders in AI research. Yeah, as I said I had the opportunity was there there was a lecturer at one of the researcher. They're one of the student to start in this area Robotics and it sounded good I went for it. And what was your specific topic during your PC? It was in an area called social learning which is applying machine learning to robotics inspired by social learning in biology. So trying to mimic how humans and other animals learn by being in a social environment as other people in the environment. And that are more experienced than them as a kind of basic idea. So and idea here with robotics is that instead of programming engineering to the robot what to do at different times give it a capability to learn to observe other things around it, whether they're human or robot teacher new training to do basic tasks by observing the teacher and so it knows how to observe the teacher and how to copy how to imitate the teacher and while it's imitating in about time. You got the machine learning algorithms that are associating my environment with what I'm doing as a out of imitating. So the next time I mean in the environment again under the same conditions without a teacher I know what to do. I know what actions to take and that's how humans learn by observing. Yeah, it's her animals thing. So that research team was very heavily influenced by biological systems. There's quite a few projects in the team around how to apply our animals learn to behave to robotics. There's a lot of confusing projects there was fun. So I got to learn a bit about LG psychology as well. That was Eddie that's right for you advance actually like Was this so this was in the end of the 90s so now yeah, really Advanced especially to combine sort of vision Translating that to the data machine learning and then applying it back in in similar settings. Did you run an experiment? Yes, I did. So there's some simulated experiences and physical currency. The department had a robotics lab with technicians and Engineers, are there three or four five robots. And so the experiments were pretty basic even though we have the the robots the hard way, they still weren't as capable as they are today. So things like avoiding obstacles trying to find light sources food some of the more advanced Labs were in other countries. We're doing more advanced experiments like playing drums and juggling. They're the kind of task that people were looking at back then so it was a good we had a lab with these robots and we could set up experiments watch the robots move around and recording things and do the research. That's great. And what did that period of your PhD what it did it teach you? That help you throughout your career how they've been pointing in Korea that you look back and go. I'm really glad I did that because I got this what would some of those things but the main ones are being independent. So as a PhD, it's a minimum of three years. Some people take longer. Mine took five of it's just you you have teammates colleagues working on their projects and you put your supervisor, but it's largely just you on the project your PhD, so it definitely teaches you to be independent to time manage project manage be coming into it. A lot of people straight out of uni, you don't have those Kills, so yeah, that's a big one. Another one is to be critical. It's probably the better one the more important one to be critical to think critically not just of other people's work, but your own difficult. That is a skill. I think it's one of the main benefits of doing a PhD, of course, if you want to become an academic you have to do a tasting but if you don't these are some of the skills that you carry through regardless of where you go, that's the two main ones that I look at. That's really good. And once you complete your PhD, where did you go? So then I moved back to Australia to do some more research. At the end towards the end of the PHD. I kind of started to suspect that Academia is not for me. And so I was that sorry. Yeah. Sure. This is something that I talk to a lot of academics and phds about that. I recruit Academia is all about Innovation. So if you're not advancing the field you can't survive and I realized that my passion wasn't necessarily in inventing new things. But rather in applying solutions to interesting problems. How's the main insights? Really and that's what I say to people that's the main differentiator there's others, but that's the main one. It's very Competitive and it takes a long time to be rewarded. So the life cycle is quite long without having a paper published or heading a grant proved often you get recognition for work, you did two years ago or six months ago if you're lucky and it's quite difficult to keep yourself motivated like that. As I said at that time. I started to suspect that and I thought okay. I'm also the confidence to going to business. So I'll get a research position that has some kind of industry elements to it a to give me more Students that I can do it and be some more employable at the end of it. So I took a research position at Monash University in natural language processing and it was an industry like a project that's down in collaboration with industry. So the business partner there was HP and we did some work on trying to automate email interactions in a call center. It was very interesting project. Yeah that had that kind of real world connection. So do that for a few years and how are you going about solving that problem back then? What did the approach looks like? We kind of focused on the 80/20 rule where 80% of the questions are the same variations of the same thing and there's book standard answers to them. So you don't need a human to provide those answers you can automate that the more difficult questions you need is a human form. So there's various techniques in NLP for doing this kind of thing. It's called question-answer techniques where you're kind of today Google does is very, well. You have a dialogue with someone you answer questions. You have a take turns answering asking and answering questions back then of course, it wasn't there yet. So It will basically broke down the emails into sentences. So they were there to the atomic units of information and then you can model when there's certain words in the question. We tend to see these sentences come up in the answer is we have a big Corpus of emails from going back five years or so and so you can see when these emails are submitted by users. These are the responses they get from the call center because they do a lot of copy paste as well. Right? So it's very strong signal, you know, that kind of that. So it was a good machine learning applied to text we predicted. From keywords. What should be the answers sounds a lot like search doesn't it? Yeah, it's the very similar but applied in a very specific domain. That's great. How long do you do that? That was about three years, you know, it's good example of you know, what I was talking about earlier about the rewards are slow. Yeah, we couldn't get papers published most of my time in that job and just when I left literally when I left everything started to come through. So we're heading a good Journal paper through some really top conferences and I actually had to go to some of those conferences after I'd already left the job. So it was nice to get the recognition of the end, but he is a slave. Yeah, so that was another key sign for me that it's not the place for me. Yeah, it was fun interesting that there that the incentives are so strange because it is super competitive. Yeah to become a researcher and academic and then super slow rewards and recognition interesting but very self-aware of you to pick up on that signal so early on the actual take steps towards something. Rent. And again, it's that drive to solve problems as opposed to innovate solutions that make sense. I realize my passion was installing problems using data on using machine learning the probably have to be fairly difficult. And the solution is in the selling to be Advanced. It's actually one of the key learnings of made it in my career after that in business. Yeah, but often the value that you bring to an organization is in solving pretty basic problem, but you saw them and you get the recognition straight away because you the business to the valuing actually, that's right Italy and reward you for it. Yeah. They're here to feedback or through the opportunity. It's very satisfying correct because you get to see the impact of your work quickly. Yeah, what are you use on the industry today? How those two sides are focused on by most people in the other two sides. I mean the research Innovation piece of creating new things versus the applied side of solving problems with an existing tool kit. Where do you see most of the focus and The people working today and what are your views on the the two competing sides? I think they're much more aligned these days. Yeah, definitely compared to back then much more aligned now, we're seeing the two communities interact with each other much more. I think the birth of data science as a term has done wonders in that space because it's giving young researchers a job to go to the snow in Academia. This is not research, but that is appealing to them. So I remember when I was looking to leave Academia. I actually didn't know how to search for a job actually didn't know. To put in the search. Yeah, what do I put in? I'm going to bring machine learning. It's in the not produce anything back then it was analytics. That was why you looked for and I don't think it's as appealing to a young researcher as the scientist the word science. It's there for a reason it's not just fancy words because the roles have changed as well. There's much more openness thinking organizations to do research to do the science. It's brought the two communities much closer together and then other things kind of like informal Community networking events meetups. You see that Two communities now interact so seamlessly compared to before and not just the young researchers, but even the experienced academics, I think I'm or wanting to go to these events and interact with industry. Hope there's more of a Common Language and I think organizations are opening up to data science research then before even things like the fact that our is used in business that has been around for a long long time in Academia. It's a tool that businesses use Python the same thing. So all these things are now enabling Alignment much closer alignment between two communities, which is great. It's really good. That's really good. And how did you find your transition from Research into history? I think it was great was very smooth. I think to some extent it's the job that I ended up in had a lot to do with it. So my boss was very open to having someone like me there they saw the value of analytics. So it was called in the small enough company that you could do a few different things different ways. So it made my transition easier and all the reasons all the suspicions that I have. Were confirmed that I'm much more satisfying being in an environment where I'm not necessarily inventing new things about solving problems real problems with my skills with the tools that I know about. The one thing that I learned pretty quickly was to embrace Simplicity. It's one of the main pieces of advice I give to the assignment Embrace duplicity or go to Academia. Yeah, seriously to the point where in my first job I was mainly using Excel it hurt to start with but I embraced it. I was able to deliver value really quickly and significantly this Excel it's racing. Yeah, that's actually really good example of focusing on Simplicity. Do you have any other examples of when you coach somebody or Mentor somebody through help them get through a problem where they were not focusing on Simplicity and you help them sort of get there to see what a simpler solution could look like or what is the conversation that you would have with somebody that's getting stuck in the complexity to look to the Simplicity. I think later on, you know, I moved on from Excel and did a lot of work in. SQL in SQL and even building some basic models in sequence and you would get a young scientist going to use our house becoming the thing and I had quite a few conversations along the lines of I want you to try it first and see before you have to go to our mind using eyefinity. But if we cannot keep it, but keep it simple as keep it in database where everything is and we can productionize more easily and where other people can look at your code extended without having to know our because many of the problems could be solved in SQL including linear regression. You can cut it in secret. Yeah. We had quite a few. To some of my favorite models are very basic SQL model and that I've built such as had a model to predict the gender from someone's first name because it's important gender is a very good signal modeling. We can always ask the customer they gender is but we have many many customers thousands over the usual for whom we do know their gender and their name. So we've come across most famous another agenda. It's literally a model it scores everything by all the genders that it seemed it's very basic probability model. Very basic very powerful, but holding second will Real model behind it. So and this couple of others, you know, yeah, the value was quick and significant, but with basic techniques, it's difficult. Sometimes I think for our scientists to embrace Simplicity. You think they want to work on the advanced? Yeah. You really need to be clear about your relations. What will drive you are you in the right place? That's right. And what type of outcomes make you happy? Are you excited? You mentioned that your first job was in a small business. What do you think about that the fact that it was a small business did it? Many advantages that prepared you that give you skills that you use later in your career. And what would be some of those? Yeah. I think the advantages are it's easy to get stuff done and it's easy to influence. So I was in a row where my manager was reporting to the CEO and the office was still pretty small. I got to interact with the see a regular basis and with all the other key Executives and stakeholders. So I definitely told me about influencing and it's just basic stakeholder skills and being my first job you told me about how to be a professional in business as I thought. Her research environment, so just basic communication skills and interaction just interaction skills when your research you're surrounded by people who are equally kind of qualified and equally minded have similar skills, whereas in business because you've got your media team that you need to interact with other teams that are of course Very widely ranging in their skills and qualifications in the type of work related. So taught me how to work together with others compliment the different skill sets and then he taught me the basics of data in research you tend to get cleaned that right? Yeah. Doing the toy data sets so they taught me that first job taught me there. What's really out there? Yeah, the challenges of very data messy. Unstructured having to know the business process before you can really make sense of the data. That's a huge one. Yeah. Absolutely. It's something that definitely carry through rest of my career you to understand what's generated and if possible go to that place where the data is generated and be there see see how its generated see the process the business process is generated and then have the relationships with other stakeholders. You know about different parts of the organization how they hide works and was their development. I don't know if opportunities is the right word. But what I'm trying to get to is the fact that you had Direct access with Executives with the CEO that immediately lifts anyone's level thinking of professional thinking that you'd be looking at a business in a more holistic level. Did you feel at the time and I'm wondering because it was your first job and you straight away had access with executive order. Access to Executives at the time. Did you feel that you were getting a higher level perspective over business and business thinking compared to being sort of a smaller part of a bigger team does thing I realize it at the time but in retrospect yeah, definitely, but I actually it actually had the opposite effect on me. I actually felt like it was all happening too fast because I didn't have confidence in my technicals about time. Right even though I done the PHD I done the research. I didn't have the confidence in my technical ability to performing a business and I was promoted because my manager left I was promoted pretty soon after like a year after to be the manager of the team and I didn't like it. I actually left that job to take a step down. I felt I needed to be more in await my needs for longer before I can take that step. I am so impressed very self aware and very true to yourself and I've seen later on in my career. I've seen other people make those mistakes too. Especially my team have been things that I've been building warning people from doing that from climbing too quickly. Yes. I know it's tempting. Of course whenever she is there is so you can understand why this plenty of time to be a manager to be a manager and executive a whole career ahead of you. Yeah, it's important to be confident in your technical skills. And also have fun. That's why we're here, right? We enjoy the technical part of it more and so enjoy those years don't rush I've had to have this conversation quite a few times with people I've seen since then mentored and managed that is so great that such a great perspective what type of things should people aim to develop. During those years seeing as like in the weeds over that technical work that they're allowed to have this fun. What things should they be thinking about developing then that will help them later in their careers. They progress into management and higher definitely working directly with the data The Source it as close as possible to the source of the data that you understand the issue of data, but ultimately that's what gets in a way of outcomes is getting in that another eighty twenty thirty percent of time spent cleaning up that are getting it ready. For analysis modeling reporting. If you don't have a real appreciation of it, you're not going to lead that assigns teams effectively because you'll keep getting frustrated about why is it taking so long? Why is this you said this would happen this way and then I'm going another way. So until you really see the data that you even know what to ask sometimes. So having a print quality use with a rolled out as close as possible to the source the standing of the issues of dealing with build-up. So things like database key data manipulation skills SQL course, definitely in those first two, Oh three years. That's all I did is SQL actually learn a skill on the job. That's pretty much what I did. I was fortunate. I had someone to learn from it was amazing. Just think about how that are moves around what could go wrong along the way, you know the input so, you know, you want to build a model for you want to show some insights. So, you know, it's going to be an input and output but for you to draw correct conclusions you to be responsible with how you get there. You have a responsibility because you're the one is touching the data. It's no good saying, oh but the website broke or the CRM broke, so my fault this field usually As M for male and suddenly it's a male or yeah one one. Yeah, it's up to you to ensure that these things are accounted for those are the things you really need to focus on initially. Yeah to get the experience on what could go wrong building that input as you're saying exactly so that when you looking for patterns of how they predict the outputs and you can be confident about drew the right patterns out the right signal and they are predictors predictive models are reliable or that your insights the process of generating and sharing insights with a business. This is reliable correct that philosophy actually very clearly see how it has made you a much better manager than people who don't do that because then you're able to help the team the team can leverage your experience of years of identifying and working through those types of issues that you can feed that back but then as because you understand it, but it also isn't the problems as new ones come up from your team. You're able to take those with you. Yeah, you know what to look for that's the only way I know to look for and you know to make sure that I have looked at everything that needs to be looked at. Yeah, they've got the skills. They're asking the right questions are being inquisitive enough of the data and there are ways that I haven't missed. That's really great. How did you feel in those early days of your working career after leaving Academia? How did you feel about the Simplicity of the work back? Then? What I'm thinking is you came out of a PhD and Ai and Robotics to work a few years and NLP back then you know, so yeah, very Then yeah and then going into a job that was around Excel and then SQL at the time. How did you feel that transition initially it definitely it hurt quite a lot that I wanted to build the machine. Like I wanted to predict things and then show the company. Hey, look we can predict these things and therefore take action adapt personalize The Experience whatever it was and I know deep inside that's what I love. I love machine learning. I love using data and clever programming to use what's happening at pass to put it was going to happen. Ultimately my passion. I was looking for all these opportunities to apply machine learning but there was the what low-hanging fruits right there everywhere that had nothing to do with machine learning talked about embracing the Simplicity. I learned to embrace Simplicity because I realized I had other passions which were just using data. I thought my passion was using machine learning to solve problem. I have my passion was using data to solve problems. So there's lots of ways to use data to solve problems that aren't the advanced machine learning as passionate about that. But those areas where it took me a while to realize it to admit that to myself. Yeah, we're getting went back to recognition you get recognized quickly for this. Because we're adding value is time the low-hanging fruits are there and so you quickly and significantly provide value. It's rewarding. I was curious why you made the time and the space for that period And I was wondering if it was patients or something else and it sounds like it's because your results oriented. So the fact that you were doing this work that it can be seen as like yes on the simple end, but you do This work and you're getting the satisfaction from the results that that generating the positive feedback loop. Yeah, that's a really good way of putting it. Yeah. Absolutely. I think that's the key difference. If someone's choose between being in business of being in research some people thrive from Innovation from coming up with new Solutions new techniques, which is fine. We need those people very nice. It was others Fine Results find the satisfaction from to solving problems everyday simple problems. No, maybe not simple problems, but using Simple Solutions and making A difference making a difference in the organization. We are now in the background. Of course. I'll still hoping to eventually be doing more of the advanced stuff to I'm going to kind of let it happen organically quickly realize also that businesses in Australia. We're at that level of maturity yet. Anyway, there's a very few places that were doing stuff. So I realize that I have to be patient and just wait for it to happen and try to steal the looking for opportunities to identify areas where machine learning could be used but not let it get to me not religiously and not let it get to me if I couldn't find it and that worked. Yeah my next step after I took that step. Down was to join an organization. That was very mature. So a company called I select here in Australia have a digitally focused comparison company lot of data lots of customers in the awareness was there before I got it was obvious to me. I was actually looking I was quite happy where I was I wasn't really looking for a job by the time I met Tony Lang who was running the team at the time I met him at a networking event and he painted a pretty good picture of what they're doing is like yeah, I want to be there because the other thing I learned the previous job was that if you're working in a place that doesn't really want you it doesn't really want that. Ants because I understand it really sure what the value is. You just spend your time selling my boss. There was a lot of her time was selling the value in the previous row. Yeah, and I'm not a salesperson. That's not the decision I made back then was to not put myself in that situation if I can avoid it to be in a place where I have to steal the value of analytics. So when I learned about all they do with Arsenic and how advanced the awareness is. I had to go there and yeah there were already doing bit of machine learning then how old was I select I started to notice about 10 years and the analytics data science team. Two people and how long since they have been established now about two years, so I came in it was like you maybe you're too old and they were already able to implement a couple of models and business one of the more so interesting and in terms of the trajectory of the organization what made that organization different was there people that were selling early on in the organization's life or where people able to get value from data science or machine learning when the team started. What do you think? Were some of the factors that led to that organization having a high level of maturity with their analytics team. They were always very mature from a digital perspective and the person found it yet an engineering background. I think you just stumbled onto analytics and he realized he was just blown away the idea the concept record of engineering thinking helped. Yeah, so I thought I'd give it a go and got one person. They showed a very well it was still very organically using open source and just basic implementations without expecting much money. One software into many people to begin with it's very organic to showing the value of with one more than another one getting another person. Ultimately. It was born by the founder hearing about it yet reading about it believing in it. And then once you got depressed at the top as we heard many times before if it starts at the top, it's a good place. Yes, it's started. I represent very interesting and definitely the fact that it was a digital native really digital business would help but obviously it was a digital business because of the mindset of the people People who started as well really interesting and between that job that you go to management and left and after that when was the next time that you went up to management? So I was at that job for three years and when I moved to my select it wasn't management. It was a senior senior role but not management and I was there two years. I suppose I started to manage them as a junior and then my my boss left Tony left and I took over the team. So let me about all out five years between that first decision to step down and Event to get back to it. Then. I feel ready five years of solid technical experience Hands-On sitting at the computer getting it back backache. Yeah, you know not really speaking to many people but just Hands On Solid technical hands dirty with a dirty data data issues that experience of chasing up by T is ways that are why is it not doing this or that and see the data? So to the end of the life cycle of a model into end solid five years of that. I felt really to now I can lead function because I know about the issues so Ting and there's a few things that are particularly interesting one that I'm really curious about is the vision and the awareness that you have of looking at what managers do and what different types of managers are like or maybe more specifically but different flavors of management there are and what skills are required for those. So the fact that during those five years of doing the technical work, they're doing that time you're able to pinpoint that there's some organizations that need a sales. Person in that analytics lead role so they can educate and others that need somebody who is driving results. Where do you think that Vision or that awareness or that Focus came from? How were you aware doing that time doing the technical work? How are you aware enough to see those distinctions those different flavors of that managers and what's required. There's a very simple answer to that which is stay connected to the community. T be involved with the community because that's how you hear the different perspectives. But that's how you hear about what's happening everywhere else and one of your initial speakers you doing the Baton ski was big mentor of mine at that time and really influence a lot of my thinking they hadn't he'd already gone through a long journey articulated help to articulate for me how different businesses operate those levels of maturity. I think you still doing that today. Oh, yeah. Yeah. He's definitely helped me in my journey a lot and it's not one person. It's you go to events. Yes. Speak to people. It's so so important of course networking is important get jobs. But that's one part of it. It's equally important for this raising that those levels of awareness and Visionary say to see the full bigger picture. You can only observe as much in the current company organizational your that's right your camera roll and you need to be observant to complete the picture you have to go outside and they'll science communities tend to be pretty small pretty tight. I think it's quite easy for us to network and to be a community. So it's definitely another one major piece. The advice I gave to data scientist stay connected to your community and also people in our space that are really nice. Yeah, I really open always willing to have a chat in to help and provide advice and it's a forum where you can get Advanced you can get complex talk about complex and advanced. Yeah Solutions and implementations with people who want to you don't have to simplify. Correct. Just a nice forum. And what did that look like for you that connection to the community. I assumed this was at least in part. It would have been before meter maid of yeah, well It prompted me to create the meetups. Yeah. So again Eugene's started the culture in Sydney. Now remember we started our user group and I remember talking to him and saying would you mind creating a video link? Because I want to be part of it. Yeah. He said to me good interesting idea. I'll have a look but why don't you start your own meet up? Laughs? Hello. So I did it. So I started the I use a group made up and then after that the data science, you know in Melbourne because it was I mean, there were some the word forums to network, but The more formal be more kind of had high end of professional scale more of the management certain kinds of Industries. Where as if we didn't have the Meetup didn't really exist back. Then that's kind of more casual open to anyone environment. We could just broke up in a jeans and t-shirt have some pizza and then we people like-minded people from anywhere any industry or any kind of organization any level both business and Academia. So we had students and lecturers business managers and analytics professionals anyone else. All right. And I think it really helped to facilitate those forums for people to be in touch with the community totally agree. And the thumb of the as in the media said you started there have been as a needle. They've been so successful but they're also been so helpful and so instrumental to so many people in the community from your perspective. What makes a good meet up. I've you crafted that cocktail over over the years. There's not that much to it Find the venue for people to get together but feels safe anyone can feel Confident turn up at that venue and it helps to have beer but definitely and food. Yeah, definitely but we do not always the meetup.com concept I think makes it available to people it gives them that it feels available as in safe if there's something that's come through there if you like. Yeah, it's going to be casual and not gonna get judged or I want feel like I'm competing or once you like how many seats are really being assessed or there are potentially interacting with the employees there for her. Be on my best behavior. Is there any more casual and I think I created I think it's just using the meetup.com concept. I need a venue finding speakers writing pieces and beers. Yeah, and at the event just being very honest and genuine about why you're there what the form is about and it just takes care of itself. I was pretty Blown Away by the response. Yeah to build both of them meetups still animal. I was a very blown away so clearly it was needed. It was a market for it. I think it's definitely helped a lot of people make connections. You don't necessarily go when you're looking for a job you go to Mike. Connections down the track if might end up in a job where I end up in a collaboration my land up in anything but you making friends. It's fun find one you learn about new algorithms you taking to hear about how people are solving problems that you're facing in a casual setting after a few years. We created some add-ons to the normal concept of a made-up such as an internship program hackathon what we call data Saint conference. So we kind of added basically can't take all the credit is very busy going often called feel brierly. There's a lot of the work. Very lucky to have him I know that the community is much better off running a lot of this stuff. It's always with it commuting one. How do we help the community? That's really good. Yeah, and the add-ons it's fantastic because so many people have gotten so much value from the add-ons and I know that for myself that the past job I built my entire team from the internship process of the data science Melbourne need up sounded fantastic as a process and very easy to find great people where did the idea for the add-ons come from? Just from issues that I was having myself. It's the same as you I was struggling to build my team and I think I accidentally had an intern once someone's done. Wanted to get some experience. Yeah, I realize well, this is something in this not just for me but for the community, it's a good model think it's a good model. Let's try it out. And so there's like a bottom up. Yeah. I had a problem that needs to be solved and luckily also I select was a very supportive over the Meetup willing to help actually and and also to help attend events and promote the program the attention We use it ourselves. I still use it. And I think it also addresses that interplay between Academia and business very very well. I think it's facilitated really well. So many of my interns were data scientist wanting to just finished a PhD or Masters and undergraduate maybe have done some research already for few years, and we're wondering whether they actually want to mix in transition like I did moving to business to celebrate that car transition for both sides really. Well, it minimizes the risk for both sides gives both. Both sides a test environment you set it up as a potential 6 months 12 months, whatever it is if it works out you got a bench to recruit from let's write some of these proven themselves so much talk has been about what we want as many phds as possible and I actually before I had the intention program I was scared of phds and I was one myself I would looked at very carefully very cautiously for the same the reasons we've already talked about. Are you really going to leave research for the right reasons often an offshore? You're not sure. So here we go. Let's give it a go. Let's test it. If you actually can end up with phds Masters well educated and qualified data scientists who have proven themselves that I can integrate into a business. In other words. They've learned to embrace Simplicity and have recognized that it's an environment that can be satisfying they enjoy that's right. I do have to say on I really admire the approach that you take that when you have a problem or a need you solve it for the community. That is fantastic so I know. No that on behalf of the community. I want to say thank you because that's that's made all those connections between people possible those job interactions those project collaborations those learnings and furthering your career that ability to see the contrast across different styles of managers that is coming up from different you and Phil and people like you guys when you have a niche for yourself solving for the community. So yeah, thank you. That's outstanding. Thanks for saying and I appreciate it. No, no. Along the way of help because people want it doesn't take much to bring people together. Yeah - you need to push it a bit. Yeah, definitely and let's go back to the time when you went back to management and your career. You said that at that time you felt ready what gave you that feeling? It's having the battle wounds of working with data, you know, I've heard you talk about the Imposter syndrome. So I felt like I know my stuff I know what I'm talking about. Now. I know what the issues are and what's possible to and I've seen some of the difficulties that my predecessors of I've had before me and I'm ready to give it a go. Now it helped that I was in a safe environment because I'd already been there for 22 years. I knew the stakeholders. I knew that I was in the company that wants me. I think they want that assigns. Of course. I had the relationships so much about being a leader is the relationships stakeholders. And so I knew that I could focus on learning how to be a leader because I didn't need to spend as much time on learning the people around me about developing the relationships because they were already quite developed. So I think if I was to go into a completely new Company in are all it would've been a different story by the said I was in a regardless safe environment for that kind of learning you me to learn how to be a leader manager having the battle wounds and the learnings from my produces. Any what was that journey of learning how to be a leader and manager. What was that? I'm feeling you I'm still on it and how has it been how easily the early days full of challenges different kinds of challenges naturally as data scientists. We prefer the technical we prefer to interact with computers. He's yeah, not with people do that's true. We're more comfortable. So it definitely takes you out of your comfort zone even in a place like isolate where there wasn't that much selling you are selling you are influencing you having to show the value constantly and you having to learn how to interact with stakeholders and with Senior Management Executives and how to be a manager to I think the most out of your team be efficient when you're facing the challenges of a good natural. We all the soft skills required you don't come naturally to us. E we need the more I think than most functions because we so little understood. Yes that assigns is not very well understood and so it's even more important that you are able to educate show the value all the time to everyone. So I struggle with that even though I had a guy the top totally yeah, what's the 40 and at times I didn't realize that I still needed to sell the value to the rest of the organization. I kind of took it for granted a bit is one of probably my biggest learning from being environment is to never stop selling many educated me. Means even if you think you already have I think in Australia, it's an unusual problem to have as most organizations you are or selling to an audience that doesn't understand. It doesn't see the know the value. So doing that first sale job was morning environment where the cell the first cell was done. It was more of a maintaining it is the stakeholders came and went we constantly have to be doing it. It's not your comfortable leaving someone you enjoy necessarily. That's right. I'm where their particular points that gave you that signal you get to a particular fork in the road that you said. I should have been selling more. Yeah, absolutely. Yeah, there's one time another one of your previous guest Scott Wilson was a CEO. Yes, an actual couple of years. He also was absolutely sold on the only message. I was always very supportive and one point in time certainly know your key stakeholders. Don't really understand what you do. I'm going to set up a meeting with me and them and you in a room and just there's a deck PowerPoint presentation that you've used before just use that shelter. She said around a boardroom table and I presented for an hour and I could see it in their faces in their eyes when they Any drop to their suddenly I right. Yes, that makes sense. We get it and I was amazed. I've been working with some of these people for by then for two three years. Yeah. I was amazed that Penny hasn't dropped previously already. Yes. So Scott really helped me with that doing good probably brand the team and the function and if you realize that you can't take it for granted. I just assume people just understood because by then data science was part of the furniture. Yeah, long time. I just assumed everyone understood the basics obviously not the complexities but the basics but not so interesting. Yeah, you can't Stop. Yeah, so then taking that time as an example. So in that hour, I mean your PowerPoint presentation. Will you covering some of the basics things that yeah the basics of some of the tools that we've already built by then. It had some machine learning some predictive models optimization model and just at a high level. It's a standard deck that I used when we have new starters in a team or when I was presenting to the industry or to investors, but I hadn't presented a too many of my key stakeholders. Yeah all taken the time to Did you pay them along the way you really need to invest in the key relationships and not just the connections themselves, but their education when they prefer to be on the tools if an enemy is a tools. Yeah, as a leader you have to make that realization that you can't be under Tools as much how it all sometimes and you have to focus all your energy and time on the selling their relationships and fluency and I really like the you said focus on not only on the connection but on the education is well really want to dive a little bit deeper into that. What are the benefits? That you've seen of building that connection side because sometimes people approach it as where I work. This is a business relationship. We just need to sit down and you know, get get stuff done quickly. What is your philosophy? What is your views on that? You chose that word connection and education. How do you approach those two sides of the relationship the commission? Yeah. I think they're very important in relationships. I don't agree with that other approach is just business now in my experience relationships that made a difference So I was it isolate for about seven years and I've seen many different orgs structures organizational structures and I've learned that there's not one right organization structure. There's quite a few that work lots that don't work quite a few that work. It's more about the people and the relationships then about the org chart. A lot of people say we can't make this work because it reports to someone else so it's never going to work. I think that's just hiding from The Challenge of connections. If you have the right relationships, you can make anything work obviously Tejada in big organizations and smaller ones. Because big organizations often when you've got the physical limitation of space in different locations. It's more challenging but in my experience if you have their own relationship to get some good stuff that you can overcome a lot of obstacles just going over and speaking to someone as opposed to a nasty email or fame will identify actually we are on the same page. It's just that we didn't understand each other which you wouldn't uncover in an email but you would in a conversation and if you have that connection the other person's more willing for you to educate what you're trying to because again that assign has a feel is it still? Everyone understood moves around different parts of the organization has its finances its sales and marketing is it central or is it distributed is likely not and because of those ambiguities tensions get created and territorial Wars, you know, what finances and what HR is legal, but when you don't know exactly what data science is where it should be it creates tension points. There's only my mind the only way to solve this by watching on the relationships of the key people that can difference also. I've always focused I struggle with many other scientists in the sub skills. Don't come naturally to us. I've got a another piece of advice is get external help to speak out to mr. Find material. There's lots of good stuff out there to help that's very good advice and what are some of the ways that you build those relationships those connections you anyways, what is the what is the U and we do it depends on the individual lots of different ways. You could be weekly monthly coffee that's in the calendar or something more ad hoc. And making the effort to go over and joke around comment about something like stuff this basic things like that. And then there's how do you deal with difficult situations where this is where that's more. Well there is where you might get some tools. I don't think that this that's not unique to data science. But for the reasons, I mentioned earlier we tend to find ourselves in just tension points more because our field is less understood in our location in our organizations ambiguous and actually very good results. A lot of this stuff is Eric basic, I agree. Please tell me if I'm wrong here. It sounds like as a general approach you focus on investing in the relationship early and creating that connection where you have kind of like some Goodwill in the bank with the person and that then they feel like you are on their side you brought in the same team and if it does get bumpy at times or there is a tough conversation they immediately start from Point of view of your well soak after me. We're in the same team rather than on developing like approaches of communication or the tools side that sometimes for example, sometimes people take quite a formal approach in the discussion or they break when they need to break tough news to somebody that sometimes we become very methodical very formal. It seems to me that you're in the former Camp rather than the latter is that is that yeah, I think people are people I mean by that we are all very similar in our fears and Ambitions. My underlying operating assumption. Is that everyone turns up at a business are there for the right reasons and with the best intentions they want to make the business succeed. Of course, there are people who have their own agendas and they play political games and there is very hard to do anything then but you can't assume that are doing it. Let's be My Philosophy you have to assume the people of their good attention. And if this conflict often it's to do with communication breakdown in communication is supposed to intention but having Journey Listen shapes you can overcome those communication break it is you need to recognize that the other person is not that different to you tell yourself. This is what drives them. What makes them stressed scared happy excited put yourself in their shoes nine times out of ten that solves that that result conflict and it's all you can do the best you can aim for us and I have nine times out of ten and just recognize that the other times well, okay, it's going to be ugly but is fantastic from a rule of thumb perspective is difficult to get any higher benefit that neither 10 times, but it's also yeah having that input She is in great great way to begin to approach and to start all relationships and develop relationships from that point of view. Yeah. It's an approach I take in life. Not just at work. I think it's just part of who I am my values really good. And before you were mentioning about old structures and that there's obviously lots of different approaches some good ones some not-so-good ones. What are some of the the ones that you've seen or that you've developed that you like and that you've seen that they work well benefited from the past. I really don't think that there is Can point to one or two or three that work because also they could work today but not tomorrow because it depends so much on the actual people that are in those are extracting even the concept of a shared analytics service versus distributed know you have the analysts in the different parts of the business. We've tried the different ones there at isolate and I've seen in other places sometimes one works and sometimes the other even within the data science team, we try different things where you try to separate the different functions in providing such as your operational day-to-day Consulting service. Us Versus Them All RND so for engineering service, do you have them separate or together? They feed off each other so much try different things still aren't convinced that one works more than the other. I don't actually have an answer. Yeah, because this one or that one correct because there is no go to Y but for example in the Consulting versus R&D approach, how have you tackle that in the past? Have you had it shared as in Split time from the same person or people or separate people that do each other? So I've had the completely share that everyone in the team does a bit of elves and you just prioritize based on the work who's good at what who wants to learn what and what is the business name and a bit of split where do one or the other and I had a rotation model as well. You can move between them then it's not one that works depends on lots of other things again to me. The main thing is you can try different approaches can work as long as ultimately business once the functions they see the value in it and you've got almost a license to try different things and then it doesn't really matter how it structure as long as you provide the value and I will try the team efficient in my experience the shared model what the best more because the people like the variety the data scientists in the tape, they like the variety they feed off the learnings from different areas. And that's when you get the best out of people engaged motivated. It presents challenges of privatization was also in terms of the kind of the well-being of the team. I found that having everyone available to do everything is the best especially when their companies smaller. The team is smaller the idea. Yeah, of course as Scale up their nose those issues are privatization and resource manager coming to it. But if you have the support of the business and then they can trust you to run between the best weight loss and through that Journey. How do you balance the development of people and giving them new challenges versus getting them to stick to the knitting and spend more time on the things that they're good at or better than others where they can get fast results and have you had moments in your team where your fluctuating in the time that's given to both of those areas and airing on one side or the other. Yeah. Well, I definitely recognized early on that. You need to have the right balance and you need to experiment a bit with it before you get it right? It's a bit different for each person to but of course, you've got to be fair at consistency. So a couple of different ways one is the way that you allocate projects to people you make sure that yeah, you know just exploiting people's strengths but you recognizing the development needs and development interests exposing them to work even though you know, it won't be done as fast. Interns on board we constantly doing because you have to give them work and whether they're to develop you make conscious decisions all the time about this piece of work is going to take longer initially. Yes this person. So that's one way the other is blue become more extreme, which is actually allocate time in a week for developed. So we had a little thing called Kegel time Friday afternoon where the team knew they could turn their emails up block their calendars and that permission to do some fractions. We call the cable time many people wanted to do some cuddling. It was good wait for dinner together. Well pick a problem and do together and then something yeah, but it wasn't just gold they could do whatever they want. As long as it's something to do with a skill that can bring back but working on an area that just didn't have to be related. Of course the same loved it, but there was actually a strong value back to the company because people learn skills and learn about algorithms approaches that then plant we had a one of our data Engineers learned about python. So you went from zero to being a python developer just from what he learned at cattle time, and he learned about machine learning not enough to build. Honestly enough to be able to interact with the data scientists efficiently. So when they were handing in their models, he was able to have conversations the right conversation. So you learned about tightening learn about machine first grade. So that's just it's a great way to maintain our balance. Yes development and just getting on the job playing really interesting how much time would be allocated to Carol time on a weekly basis kind of varies, but between two and four hours on a Friday afternoon, sometimes we would kind of aggregated and do a hot date so we would kind of Up a few and then do I have day when things are busy? You can't turn off your emails. So it'll be times where it was those ups and downs but as long as me as a team leader made it clear to them that they have my permission to do that in knowing that they can make a difference but it's also how big was the team when you went into management to Leading it when I joined this three of us and I took over the 5 and by the end of 50 and how was that period of growth between 5 to 15? How's that period for you full of learnings both in terms of yeah, the stakeholder management. Business side of things and also in terms of being a manager obviously ups and downs and good challenges and mistakes successes that when I left it's pretty happy very proud of a good combination of here data scientists engineers interns really good also different levels senior Junior. Okay. I've learned pretty quickly to zip want to create a single layer. And if you don't run it especially scale to help so you can focus more the strategy and the stakeholder the influencing because you can be less Hands-On. That's right and from a from a team leader. A shape or Team Management perspective. Was there any particular or specific key lessons that you learn cleaner job. Yep. So as one of them, is that support layer. Yeah. See you later. I learned pretty quickly to get the team involved with recruiting interesting. Yeah. Yeah an early days. I don't know. That's my job. Yeah, that's nothing to do them. And I could have a couple of people in the existing people in the team resented me for it. Remember the pretty tough intense times not necessarily because I didn't like the person because they weren't involved. When Consultants I learned pretty quickly to evolve into the point where now or towards the end when we were recruiting for interns everyone in the team got involved with meeting and seeing their presentation helping the scoring selection. There was a queue Tony and I think it's because the sound is that you look for are passionate people. That's the number one. I think actually the you look for because it passionate they're passionate about a lot of things. It's not just about that a science you need to address that passion and that passion be translated so that to be wanting to ideas heard wanting to have An influencing the direction of where the this the team but the company is going we often have people who want to speak to the CEO one of the time with Executives even though they might not be ready for yet. But you can you get that yes important. Let's do it. I think the other thing I learned is to kind of recognize what kind of leader you are. We spoke about this a bit earlier to recognize other leaders, but recognize what kind of leader you are and have strategies the suit you and suited to each individual person that you're managing. You can't just make that stuff up you need to allocate times with to have a strategy it does. Always have to be complicated or anything, but just to be mindful of this think about this stuff and get external help ya try and find a mentor externally and internally to help what would be some of those strategies. What does that look like recognizing? What kind of personalities they are about to you? Yeah. And when do those personalities Clash? When do they work? Well together. There's very kind of methodologies out there to help with that one that I like is called disk D is see mean it's it's recognizes four personality types. Sure. Remember which one stands for Saudi dominant eye is influential accessibility and D is kind of see at the end. Sorry C is correct. Cautious option is incorrect yet, which is the analytical one. Yes. It's actually even though it's four things as a Continuum. It's actually like a it's literally a disk. We're like a circle we can be strong in a couple of things and we can others but you can place yourself on the circle and then you can place other people in the circle to and their strategies for people. More in the right hand side of the circle. How do they interact? Well people in the top left or bottom left or whatever and the clients. I find really actionable tools that they provide you this is one example, there's any other end I think it's worth investing the time and again, it's not something that you enjoy doing. This is a really I think it's really important. I learned that and do you remember what was your this profile? Yeah. I was I mostly S. I like this really I like to keep the peace. So I do tend to avoid predation, but it's also related. Add to running liking routine or that stability from like your day-to-day knowing what's coming. It's interesting because in both of those are very people focused because traditionally the I the interpersonal or influencer hissing kind of like I said the extrovert liking to hang out with people on the experts type and then the S is not necessarily an introvert. It's usually people that will go to the party will go to the Gathering they don't need to be the center of attention, but they like Getting to know people mingling and does it also be there to keep the peace to help resolve. Yes, where's the season had to be more dangerous, correct? So interesting, I do find this stuff interesting. It helps the him. My point is that it's worth investing in even if you're not interested in it, it helps like you can't ignore it. So interesting, so mine is driver Saudi and I your interpersonal exams very very closely aligned and for a long time. I was quite uncomfortable because I So the see as the analytical piece so I was like, whoa. What am I doing working in analytics? If I'm the another goal in this Behavior one isn't like a strong strength of Mind actually and you're probably D but close to the season. Yeah, I looking at I know quite a few data scientist already, so don't worry. Yeah. Good good, correct. Yeah, that's a really good point. It is important to invest in this thing another. Not my business to always focus on retention never lose sight of which many different ways different retention strategies because let's face it. The scientists are in hot demand and Recorders can be quite aggressive and it's quite a challenge to see youngsters get easily distracted by someone else's Shiny Toys distracted by money to but not a thing as much the hype doesn't really help in terms of you know, the big salaries that's not always the case, but I think it's not just the money. It's being distracted by someone else's shiny toys and when They're young they're susceptible to that. So you have to be mindful of it and make them realize to be conscious of it to and work on providing an environment where they wouldn't want to lose the best place possible. It's one of the pieces of advice I provide as well to Young Dar scientist while I accept that. It's important to try and different experiences when you're young it's also important to see things through not get so distracted. It's easy to think that something is better over there but facing the challenges where you are is equally important as a professional develop to face challenges and overcome them. And how to overcome them see things through and yeah recognize the good stuff. Yes, when you do that is very true. Seeing things through that gives you a lot of learning and really solid experience because I have heard people in the past say I need to look for another job because I already know how to use every platform technology in the team, but that's usually very short for this is too frustrating the doubt as to my CIT keeps getting in the way or our stakeholders just don't understand this and it's easy to just give up and think they're little going to be better somewhere else or you hear that someone's doing something cool particular technology that they're using or certain kinds of machine learning that they're doing only to get there and realize that you know, they don't even have a proper bi environment. It's easy for the youngsters to get disillusioned and distracted having the discipline. Is this a challenge like something I mentioned in your current organization like the data is always to miss you. I think it's getting it's a good idea to work on us find ways to overcome them because most organizations have those same issues. So I try to encourage them to see Through and embrace the opportunity to learn develop from not give up too easy to quickly. It's really great advice as awesome you are that is an excellent note to end on this has been outstanding. Thank you so much for your time and for sharing all your wisdom and all your learnings. It's been truly fantastic. Thank you so much. Thank you. It's my pleasure. Thanks for having me. You're going to be chatting to you. Are you to thank you so much. Thanks. That is all services is Australia's leading executive Search and recruitment provider to the data and analytics industry data source is chosen by many of Australia's most successful and Innovative analytics team working closely to understand customer needs and deliver the top-performing candidates in the Australian Market from Executives and directors through the project managers Bas and Technical Specialists are deep networks allow us to Source the highest caliber of candidate our consultative and personalized approach to the recruitment process. Choose the highest level of service and care across both Contracting and permanent roles, whether you're looking to hire or searching for your next career move. Please contact will at datasource services.com you for more information exciting news listeners University of New South Wales has launched a new master of data science and it's a hundred percent online. They have designed this program to deliver the skills that are in the highest demand and most difficult to find it covers the advanced stats programming machine learning and strategy are He has you need to be able to call yourself a true data scientist to find out more visit study online dot unsw dot edu dot a you. That brings this episode to conclusion. Thank you so much for listening. Please find us on data futurology.com or on Facebook Twitter LinkedIn or Instagram as that of utility. Also go to data futurology.com forward size podcast to find the show notes for this and any other episodes if you liked this episode, it would mean a lot to us if you could leave us. Review wherever you listen to our podcast. I hope you enjoyed this episode and that it was helpful and valuable for you. Thanks again and see you next time.
Yuval is an Analytics and Data Science professional with extensive commercial and academic experience. His interests and goals are to be working on interesting and practical problems where there is a need to discover and act on meaningful patterns in data, through advanced analytics and data science. I'm the founder and co-organiser of two meetups: Data Science Melbourne and MelbURN, a user group for Melbourne-based users of the R statistical and data mining programming language. In this episode, Yuval tells us about how both of his parents are statisticians and inspired him to fall in love with data science. Growing up, he used Pascal to build spaceship games, and it motivated his passion for programming. Eventually, Yuval went for his Ph.D. and focused on applying how animals learn and behave to robotics. Simulated and physical experiments were pretty basic because robotics were not as advanced as they are today. Later, Yuval realized academia was not necessarily his calling, he was more interested in applying solutions to interesting problems. However, in recent years, research innovation and solving problems are becoming much more intertwined. Enjoy the show! We talk about:   [01:40] How Yuval fell in love with data science  [05:45] Social learning in biology  [08:05] Lessons learned from completing a Ph.D.  [13:10] Research innovation vs. solving problems   [15:40] Embrace simplicity    [18:00] Small business advantages    [21:45] Skills to develop before management    [26:00] Results oriented work   [30:45] Different flavors of management   [32:50] Connection to community    [40:20] Learning to interact with stakeholders + managerial skills    [44:00] Benefits of building connections + education    [48:00] Assume people are at work with good intentions    [52:00] Allocate time for professional development    [59:30] Focus on retention     Resources: Data Science Melbourne  MelbURN Yuval’s LinkedIn University of New South Wales  Thank you to our sponsors:  UNSW Master of Data Science Online: studyonline.unsw.edu.au  Datasource Services: datasourceservices.com.au or email Will Howard on will@datasourceservices.com.au  Fyrebox - Make Your Own Quiz! Thank you so much for listening. Enjoy the show! 