Welcome to the SuperDataScience podcast. My name is Kirill Eremenko, data science coach and lifestyle entrepreneur, and each week we bring inspiring people and ideas to help you build your successful career in data science. Thanks for being here today and now let’s make the complex simple.
Hey guys and welcome back to the SuperDataScience podcast. Today I’ve got an interesting episode lined up for you. I literally just got off the phone with Michael Colella who is a business analytics consultant and he travels the world. We were actually right now, as we were talking, he was in Stockholm Sweden and he’s getting on a plane to go back to Chicago for Thanksgiving. It was a very interesting podcast and what I really liked about today’s session is how driven Michael is to grow, not just in his career but in his life as well. And we talk a lot about that. If you look at his LinkedIn, you will be shocked at the amount of courses and amount of certifications that he has done and is currently doing. He is currently a consultant and he is still at the same time doing his master’s. He’s studied neuroscience, he’s studied business, he’s studied finance, he’s studied analytics, he’s doing a Master of Analytics right now and at the same time he’s studies on Coursera, on Udemy. He does different types of certifications for work and outside of work, a very interesting life-long learner like a lot of us listening to this podcast. I’m sure a lot of you guys are also life-long learners. We talked quite a bit about that. We also discussed how he integrated his passion for travel in his career and I found that very interesting and very inspirational as well that he knew that he was passionate for travel and he managed to build a career for himself that included that component, which is very important that we always do what we love and what we’re passionate about. We don’t sacrifice our passions for other things.
Another interesting thing that came up on the podcast was a break that Michael took during his life. For three months he went away to another country just to reassess his life and what he wants, and to align his future strategy in how he’s going to build his career and other things. So, a very interesting podcast overall, can’t wait for you to check it out and without further ado, I bring to you Michael Colella, Senior Business Analytics Consultant.
[Background music plays]
Kirill: Welcome everybody to the SuperDataScience podcast. Today I’ve got Michael Colella, a business consultant from all over the world, on the show. Michael, welcome to the show, how are you going today?
Michael: Thank you very much, Kirill. I’m doing pretty well. I’m out here in freezing cold Stockholm, Sweden. It’s great to hear from you and be on the podcast.
Kirill: That’s awesome. It was really cool. When I started this podcast, usually I say hi with video, and I was like Michael, are you in a hotel right now? And it’s funny because I’m also in a hotel in San Diego and you’re in a hotel in Stockholm. It’s just a funny situation, I think.
Michael: Absolutely. I thought that was pretty funny as well.
Kirill: Cool. Your flight got delayed, right? Is that what’s happening?
Michael: Yes. I was supposed to fly home to Chicago for the Thanksgiving holiday in the States yesterday and there was a massive delay, and we found out the plane was basically non-functional, so 200 people scrambled for hotel rooms. I was lucky enough to find one near the airport.
Kirill: Thanks a lot for waking up at 4:00am to jump on the call today.
Michael: No problem. With pleasure.
Kirill: What were you doing in Europe, if it’s not a super-classified secret?
Michael: I’m currently working for a supply chain and logistics consultancy. We build optimization software and advanced planning and scheduling software to solve complex planning puzzles. My current project is working with an aviation client in Stockholm, Sweden, so I came out to the Netherlands for a while where our home office is, that way I could easily go back and forth between the client’s site and completing work with the team. We had some meetings this week with the client in Stockholm and the flight just got cancelled. I’m lucky to still be here on Thanksgiving.
Kirill: That’s awesome. Oh yeah, it’s Thanksgiving so you’re not going to … Well hopefully you’ll get back before it’s the end of the day on Thanksgiving.
Michael: Yeah. Absolutely. I’m trying to surprise my family, they don’t know I’m coming back.
Kirill: Awesome. It’s really funny how you’re working for an aviation client and at the same time the plane got cancelled. It’s like an ironic situation. That sounds pretty exciting.
Tell us a bit more about yourself. You seem to have a very interesting career, or very interesting role right now where you’re consulting companies- I’m just reading off your LinkedIn – in countries such as Netherlands, Sweden, Germany, Italy, Brazil, Canada, Colombia, Uruguay, China and Spain. That’s a huge list of countries. How did you end up in this position?
Michael: Ever since college and before, I really had a strong international focus, so over the last seven years of my career I’ve had the opportunity to work across different geographies with diverse teams. Something that I’m really passionate about even outside of data science is international travel, languages, and working with people of diverse cultures. I find that very inspiring. I’ve had projects and different initiatives in a lot of those countries and had the pleasure of working with people from those countries and on to my project teams. I think it’s had a huge impact on my career.
Kirill: I really respect that when you’re passionate about something, travel and languages and cultures, and then you integrate that into your career, you find ways to make it happen. Your career is a huge testament to that. That if people are passionate about something, they can get it. Where there is a will there is a way, and it’s really cool. Walk us through this. You studied at the University of Chicago. What did you study there and what happened afterwards?
Michael: I’m currently a master’s student in the Master of Science in Analytics program at the University of Chicago. What we focus on is everything from mathematics, behind different tests and approaches to data science and analytics to the actual communication side, to also things like deep learning and machine learning and time series analysis and forecasting, and advanced Python. These are all topics I’m quite interested in, I love working on these topics and I really just aim to continue develop proficiencies with all those different concept areas.
Kirill: How did you choose this degree? It sounds very good.
Michael: My background, started off in medical research doing neuroscience research on both cognitive and behavioural neuroscience research during undergrad. There was a big focus on analysis in order to present findings. From the beginning, I had a background in applied statistics and kind of a research or analytical mind set, and I decided that as my career progressed and I got work in consulting on the tech side of things with SQL and Teradata, and Microsoft SQL Server, and some different BI tools, that this is really what I like to do. Then I eventually explored quite a few courses on Coursera and Udemy and then also including the SuperDataScience set of courses. Really, after taking enough of them I just decided I’m serious enough about this, where I would like to get a formal master’s degree. While I don’t necessarily see it completely necessary for success in the area, I thought it would help build a solid foundation especially going into job interviews, having that as a reference point.
Kirill: Okay, gotcha. That’s a very interesting progression, from neuroscience to now deep learning and AI and statistics and things like that. I also see you studied at the Harvard Business School in business analytics and finance and economics. You’ve done everything, man. This is crazy. You guys, you’ve got to check out Mike’s LinkedIn, he’s studied for all his life. It is like so many different universities that you’ve gone to. Is this something you just do for fun?
Michael: I’m constantly learning, and I’m a very curious person. The thing that makes me laugh now as a 29-year-old is looking back. During undergrad I wasn’t somebody who studied and knew exactly what they wanted to do, but I did have a trust in the sense of, I will find that out through trial and error. For me it started off with maybe the assumption I would study medicine or business, coming from the family, studying the human brain, my undergraduate major and minor were in psychology and biological sciences. That’s where I got the neuroscience flavour of things and then as I took more statistics courses and then post-graduation took a lot of learning outside of my 9:00-5:00, I think it just boosted my career. When I saw that value was there for my career, it just inspired me to keep going with that. I think eventually I’ll pursue maybe a doctorate but I’m taking it one step at a time.
Kirill: Gotcha. That’s really inspiring. Looking back, because you’ve studied so many different things. Life might change in the future but right now it doesn’t look like you’re going to be a neuroscientist or a psychiatrist or psychologist. Looking back, do you regret choosing that career path at the very start?
Michael: That’s a great question. I get that question a lot, and when I think back, I definitely don’t regret it. Starting, studying that psychology and neuroscience, it definitely had a formative impact on the way I think about things. I think right now and into the future, my interest is to build stronger competencies in AI and then that’s really where I want to see my career go. I think psychology has a direct relation to that. I think one of the most complex things that we as humans try to understand is the human brain. What I saw with different psychology courses and actually working with patients with various mental developmental disabilities or disorders, is just how complex things can get. So I think there’s that component and then also just the team leadership component. I’m one of those people that believe there is a value to a liberal arts education that’s not dead yet. I definitely have a strong mathematics background, but I think that background in psychology has helped me understand teams and lead teams and really try to focus on the different ways I can motivate teams.
Kirill: Okay. That’s a very apt answer. I totally agree that deep learning and AI have a lot to do with psychology and that will definitely be helpful down the track, especially as these fields evolve. Tell us a bit more. You’re still pursuing education, it feels like it’s a lifelong thing for you, which is very cool, I think that everybody should be like that. But at which point did you start thinking about building a career, starting a job, how did you get into consultancy? What was your first step in that direction?
Michael: After my first master’s in Psychology, I took a bit of a break, you could say, to Brazil. I started volunteering to teach English in the favelas, which are the slums. I really wanted to take that time to think more deeply about what is it exactly I want to do and what is my passion. I also wanted to make sure that I didn’t just blindly follow a linear trajectory. I wanted to do something interesting that if anything else, I could look back and say, hey, those three months were worth it. For me what that time served as, is a time to think deeply. Did I want to continue down the more medical type route or did I want to try to leverage these skills that I picked up and developed within the scientific community in business? When I got back to the States, I decided to definitely go with the more business flavour and then obviously that international experience inspired me to get involved with companies with those diverse teams and that offered me the opportunity to travel internationally. I figured that consulting would be kind of the reflex as far as what to get into. I feel like consulting is nice because it respects diverse backgrounds of individuals. You might be a chemical engineer that wants to go into business and there is generally a home for you within consulting. Of course, there’s some core skills to develop there but I think that’s been the natural fit for me.
Kirill: That’s really cool. There’s so many things I want to talk about right now, like branching out of what you already mentioned. But just quickly, so you came back and did this job offers just fall on you or did you have to look for them yourself?
Michael: I would say they definitely didn’t fall on me. There was a period during which actually I would say it was a bit difficult to find the right role. That was probably due to maybe a slight lack of clarity on my end, as exactly where I might fit in. But eventually I found that out. I think that’s really where perseverance came in to say okay, I’m exploring different opportunities, interviewing for different types of roles, I’m going to find something that fits. Then that further inspired me to continue my education because I thought, hey that’s not only going to make me more marketable, taking classes from either a business or a data science standpoint, but it’s going to further develop my skill set and give me an edge on people outside of the 9:00-5:00. I’m a firm believer in whatever you do between 6:00 and 10:00 will really determine your future, and those are the first principles I tried to use going forward. And I think it’s worked out so far.
Kirill: I’m glad you touched on that because I was about to ask, was it hard to combine a full-time job and education at the same time. Did you have to make sacrifices in order to get through that?
Michael: The major sacrifice was on sleep. My sleep took a hit but luckily, I’m able to function pretty well on about five hours a night. The last two weeks I think I averaged about three, three-and-a-half, which is not ideal. It just takes commitment. I think once I found my passion especially as it relates to analytics and business and data science, it was easier for me because I didn’t feel like I was necessarily sacrificing something in a painful way, but sacrificing something in a way of, hey, this is really what I want to learn more about, this is really what I want to do. I didn’t want to let anything stop me.
Kirill: That’s really cool. I think everybody has that time through 6:00 and 10:00 and a lot of time we spend it doing the wrong things or not pushing ourselves. Like sometimes you’ve got to rest and relax but I have friends who just watch TV or just go to the bar every night or just do nothing and I think it can be put to good use sometimes. It doesn’t necessarily have to be always, you can’t always be working and studying, but sometimes, occasionally you can and probably should.
A couple of interesting that you mentioned. The one I want to start with is the whole taking a pause and going to Brazil and teaching English for three months. That’s such a cool thing. I think so many people, myself included, would benefit from that. That would give clarity, that would give a time to reconsider things, assess things. Tell us a bit more about that. If you’re talking to someone who’s never, ever, taken a pause in their life and they’ve always gone like school, uni, maybe they did a gap year but that was more for fun and travel, and then they get one job, another job and so on. How would you help a person like that plan something like what you did for themselves? What are the things to take into consideration?
Michael: That’s a great question. I think it’s really important to take that pause and also to just expand your comfort zone. That was a huge reason why I decide to go there. Looking forward, I feel like one thing that inspires me, I feel as someone gets older, by default you have less time. Whether that means literally or based on different commitments. For me I wanted to at least if nothing else, take this time to experience something that’s maybe non-traditional. There are definitely organisations people can reach out to, to sign up for different types of volunteer activities. To be honest, at first, I was just going to go to Italy and teach English at a camp there. But I had been to Italy a number of times already, my dad has an Italian background, but my thought was, let me do something completely different and something that makes me feel alive. I didn’t speak Portuguese at the time, I had never taken a Portuguese class and I didn’t know anybody in Brazil, but I found an organisation through New Zealand that paired me with an in-country volunteer organization, kind of as an intermediary. I would say that’s something that people should think about. As, hey, do I want to do something different before I plug back into the matrix, or do I want to maybe take some time to think about what it is I really want to do? At the time different family members and friends thought this guy is crazy, why is he doing this? But I would say that would probably be the single thing that had the biggest impact on my career as well as my mindset related to my career and then just my personal development. It’s hard, at the time, to see maybe just how big the impact will be or convey that or articulate that to people, because it’s impossible to predict the future with 100% accuracy. But I would say that just believing in yourself and saying, hey, I know something good’s going to come of this because I’m going to literally will it to happen. And then it did. It’s come up during job interviews and it’s always gotten that extra pause and that additional discussion as well as interpersonal interactions with other people, with friends and new colleagues.
Kirill: Gotcha. You didn’t know Portuguese at all when you went there. How did you teach English, how does this work?
Michael: There is an in-country organization that connected us to another non-governmental organization in the favelas. Basically, what happened, it definitely adds a layer of complexity. At first, we started teaching a lot of teenagers as well as little kids. They have a lot of energy and they’re not speaking English, so it kind of forces you, it puts that extra pressure on you to at least learn the basics, so you can communicate. But there was also a willingness to learn, so we were able to convey especially with at first the help of a translator and then Google Translate, what different words were in Portuguese vs what they were in English. The kids seemed to be interested because they see all these English-speaking movies and TV shows and listen to music in English language, so they are kind of by default motivated to learn more. Then it was really just delivering on that and then I really believe sometimes the best way to learn things is to just jump right in the pool and try to swim. I was surrounded by Portuguese all day, every day. There were some people that spoke English, but I would say it was less common at the time, it was just before the World Cup. It really forced me to learn more and quickly, when I got there I was even dreaming in Portuguese. I felt constantly stimulated and for me, just because I’m pretty hyperactive, that kept me interested. I knew Italian and Spanish so for me it was just a matter of listening a little bit more closely and then seeing the words in Portuguese and then just changing the sounds. No doubt a lot of the words are very different from Spanish or Italian, but I initially picked it up by ear and then when I got back to the States I took some formal classes.
Kirill: Gotcha. But for someone who doesn’t know any other languages apart from English, do you think in three months they can pick up Portuguese to a good enough level?
Michael: Yeah. I definitely think so. Coming from a full immersion perspective, that’s the best way and the quickest way to learn. I think a lot of people start with taking classes, maybe they go once or twice a week and have some homework in their home country, which I think is good to lay a foundation but complement to that, you could actually go visit the countries or try to live there on a short term or vacation there on a short term and immerse yourself in the language. Or do what I did and just go kind of blindly and then try to scale up from zero very quickly. I definitely think it’s possible and it’s worth a shot.
Kirill: That’s so cool. That’s really inspirational thing. I’m just going to ask one more question in this because it’s so new to me and a very interesting area. When you go overseas like that, do you still check your phone, check your emails and so on, or you just cut everything out completely in order to focus on whatever you’re contemplating for those three months?
Michael: I would definitely say there were periods of being completely disconnected that were very liberating. In Brazil at that time, it wasn’t as easy as it is now to have a certain cellular provider. I’ll keep them unnamed, but they provide connectivity in 144 countries etc., it was more of a thing where, hey I need to get an in-country phone and kind of a pay-as-you-go. That was a wonderful experience at times to be completely disconnected and fully present with the people I was with. I felt like it forced me to learn a lot more about them and focus on that truly human experience instead of constantly being distracted by notifications. Actually, that was one of the hardest things to adjust to coming back to the States, was now people expect me to be connected all the time. You get used to it again, but it was just a brilliant experience.
Kirill: Fantastic. Thanks a lot for that excursion into the world of going and exploring yourself, and understanding what you want. Let’s get back to your career. Once you came back, you were in consulting, tell us a bit more about what exactly it is that you do. Of course, without disclosing any sensitive information or practices, but just out of curiosity, what does a consultant in analytics do that you travel the world, and what kind of projects do you work on?
Michael: In my current role, it involves working on different projects within supply chain and logistics globally. For me, in my career, I’ve always marketed and felt comfortable being somewhere in between what I would view as the traditional software developer and someone completely on the business side. I think that spot right in the middle is really what analytics is today because there is obviously the technical proficiencies and the comfort with coding and reading code and interpreting different types of analysis, but also the business or strategy or communication side. Being right in the middle is where I have functioned on different teams over the last three to five years, and that’s kept me super interested and varied up my day and my schedule a bit so that’s been great. Currently, the organisation I’m working for will be working with companies not only from the aviation standpoint to maybe optimize their workforce planning, aligning with flight information systems which as I saw first-hand, flights can get cancelled, and then also working with ports and container terminals, manufacturing processes. Analytics and computer science is definitely applicable in these areas because all of these companies globally are just trying to … they use the word digitalization. I’m not quite sure if some of these terms are words officially but they’ve become buzz words or industry terms where, hey, they have these setup processes and not only are they trying to optimize them, but they’re trying to get planning out of excel or more manual planning. That’s really the value that we add currently, we help solve these advance planning and scheduling and supply chain puzzles from a technology perspective. Prior to that, a different company I worked at, the teams were quite diverse, and we had overseas teams, but the client I was at was in downtown Chicago, it was a major healthcare company and even within that, there’s a lot of different tools we used from SQL to Teradata to concepts like working with data lake or DUP. But also, it’s quite interesting to be able to formulate the proper message to the business stakeholders and internal team that might be a bit more technical. I was really used to bridge that gap and it’s been the right fit.
Kirill: Okay. That’s a really interesting description. I’m very curious. Can you give us an example of a supply chain puzzle as you said, just hypothetical? It doesn’t have to be a real project that you’re working on or have worked on, but a hypothetical example of a supply chain puzzle that a consulting firm like yours would address.
Michael: Absolutely. I’ll resist the impulse to generally talk about the current engagement that I’m on. While I do think it’s quite interesting, but to take care there. For example, let’s say a major canal in the world or a container terminal. You’ve got these asset ships coming all over the world, whether they are from Singapore or Shanghai, or the port of Rotterdam, or somewhere in Australia or South America, to different locations. They have their own on-board computer systems and they also have a variety in scheduling, but they have a variety in their cargo. They might be carrying hazardous materials, they might be carrying perishable materials, they might be carrying more traditional consumer product goods. All of these containers are all stacked on top of each other, so it gets pretty complex because you’re basically dealing with a 3D puzzle where you need to be able to identify when this vessel comes into port, to berth, which is one of the terms that we use, it’s just when the ship is aligning with the dock and getting ready to be unloaded. You need to know where these different containers are and where these containers are going. So, one big ship that maybe comes into the port of Rotterdam, might have a few hundred or a few thousand containers and these containers all have to be accounted for. They have, like I said, different types of goods so they’re located in different areas of the ship but also, they all have their own end-destination or maybe groups of them have their own end-destination. The puzzle lies in being able to unload the ship in the correct order, or the most efficient or optimal order in order to make sure that these containers get to their final destination but even just their intermediary destination. Trucks are coming into ports to pick these containers up, there are forklifts, there are automated cranes that will go and try to unload the ship based on data that was received on where a said container is located. Then on top of that, there are all these complex labour rules and regulations, so these ports might run 24 hours a day, 365 days a year to make sure everybody gets the food and the products they need. You have to factor in all these unique constraints as we call them, within countries in different areas of the world from the labour rules and regulations to union rules and regulations, which include like different rest periods that are required and different breaks as well as the length of their shift. These software optimization solutions, they have to account for all these different variables from the actual labour rules and regulations, to the planning at the ports or container terminals to unload these vessels, which involve a number of different components to actually consider the information of the vessels. What’s on the ship and where it’s going and what is the timing for that ship? How quickly does it need to be unloaded etc. There are just so many more layers to the puzzle than even I initially thought, coming into the role but it’s been great to learn a lot more about supply chain and logistics and how analytics and computer science have a role.
Kirill: That’s crazy. I can’t even imagine how massive the software would be and how long it would take to create it in order for it to correctly account for all these different details that comprise this whole operation. From your experience, how long does it take to create a piece of software for solving a puzzle like that?
Michael: Definitely it takes a while. These puzzles they have these sub-puzzles. They might specifically bring us on to optimize the workforce or they might specifically bring us on to optimize the stock yard planning for what’s going on for unloading and loading the vessels. The length of a project or how long it takes to build a solution really varies. Are we building the whole thing, which would probably take a couple of years at least, or are we building for a scope of work that’s just a sub component which I would say at that point will take anywhere from half a year to maybe slightly over a year. It really depends how complex the puzzle is but those are probably the general ranges that I feel comfortable with.
Kirill: Very interesting. All right, that’s a very interesting line of work and it’s very different to what we’re normally used to in data science like R and Python programming and things like that. Can you tell us a bit about the tools that you use in order to accomplish these objectives?
Michael: Yeah, absolutely. The current organisation that I work for, we partner with a specific software provider called Quintic, they’re owned by Dassault Systèmes, I can’t speak French but Dassault Systèmes or DS, they have a lot of common engineering tools or programs that are used, specifically the Quintiq software, it solves advanced planning and scheduling puzzles across all sides of supply chain planning and logistics. Then we have some in-house tools that we have developed for rail cargo optimization. Those are the actual software platforms and then within that we interface or we can connect to any system. There are definitely SQL components involved, so you could be talking about Microsoft SQL Server and then a lot of the clients that we work with, there are specific BI tools they use. Of course, the super common one is always trying to get their planning out of excel, but really we just take pride for being able to interface with any systems that they might have as well as file formats whether they’re XML or HTML or JSON. It’s really a variety of systems and integrations that we work with, but at the same time the actual software that we develop comes from Quintiq, so they have the world record on solving a lot of different puzzles. It’s really a puzzling software that’s quite nice and then, like I said, we have some in-house solutions for some sub sets of tasks within supply chain and logistics, mostly in the rail cargo space. But there are some other popular softwares like AIMS, I know BCG they use AIMS and some other tools.
Kirill: Okay. When you say you develop software for them, what I gathered is that you don’t sit down and code something in C-sharp (C#) from scratch or in Java. You actually already have these programs, platforms, in which you kind of just … It’s a more high-level tool where you don’t need to encode all the mechanics of the tool itself, you just need to encode the problem of the client. Is that correct?
Michael: I think that’s a very true statement. The language that’s used for this software platform is called Quill. I’ve heard it described in different ways, but I’ve almost commonly heard it’s some sort of mix between Java and C#. It is object-oriented, but we’ll basically encode, like you said, the actual puzzle or the solution to the puzzle or some combination of the two, and there is the whole software development lifecycle of gathering requirements to writing technical documents that can be followed for the development processes and then also writing the functional or more business type of documentation and it’s really beautiful when the whole solution comes together. Definitely it takes a lot of hard work and a lot of listening but that’s pretty much what we do to build a solution.
Kirill: Okay. How long did it take you to get the grasp around how to do that?
Michael: I would say the whole training process it takes at least for the first level of certification, maybe about three months. Looping that in with other work that you’re doing. Like many things, I think there’s a natural progression of learning how to use different tools and interact with them and derive value from the data with them. There are formal certification processes to go through with our software partner to feed to our proficiencies and then that’s something that the clients look at, certifications, they serve to provide trust with the clients you’re interacting with. The first level, three months and then it gets progressively harder, there’s more work involved to get the higher levels of certification but that happens through time and actual project experience as well.
Kirill: Okay, gotcha. Out of the soft skills that you use on the jobs which are obviously very important because you need to get that information before you can go and do the technical side of things, what would you say is the most important soft skill?
Michael: I would definitely say listening. There is our standard industry solutions to a lot of these planning puzzles in my current role that require customization, and that customization piece is key, so that’s where that listening skill comes in. Then being able to communicate that, not only back to the client so that they’re confident that you understood them, but communicate that to your team, which is a diverse team; people who studied econometrics to traditional developers, to people on the business side. It’s always interesting communicating with people on your team with different mind sets, experience and background but also like I said, being able to listen to the client is super important, that requirements-gathering. That way the analytics that are conducted can be done in the right way and really serve a business purpose beyond just being an interesting problem to solve.
Kirill: That’s a very interesting description and I totally agree that you need both. You need to be technical and you need to be able to speak to people in order to get that information that you need or convey the information back to those who you’re dealing with. What I wanted to talk about next is, you mentioned certifications. You need a certification that takes three months to get that, then the next one is harder and harder. What I see on your LinkedIn is that you’ve done a lot of extra certifications, you’ve done close to 10 or maybe even a dozen courses on just Coursera alone. Obviously, that’s in addition to your studies, in addition to your work. What keeps you going, what keeps you motivated to do more courses on Coursera?
Michael: I would say, just looking at even just data science and analytics job descriptions as well as consulting positions related to that, these days there’s just such a “word vomit” of requirements, just everything. I’ve seen in practice that it is true that they’re going to list their Christmas list, but you don’t necessarily need to know how to do every single one of those but understanding the data structures has been key. I think that translates to all these different certifications. The approach I’ve taken is, hey, I understand the data structures related to this already or I need to take these courses to have an increased level of comfort with data structures in a certain way so these courses, again, really came out of looking at different job descriptions but then also I think that foundation in data structures is important because then you can go in and learn these different tools a lot more easily because you’re understanding, okay this is what’s maybe standard or I’m used to and I just need to tweak that thinking a little bit to use this tool, and this is how this tool will respond or this language or this platform will respond to this slight tweak. I think that’s really what it’s been for me. And then also I’m just super curious. I feel like the more I learn, the more I realize I don’t know, and that’s been a very humbling experience for me, so I think it’s this idea of kind of the “open sourcing of education and knowledge”, it’s just changing the world. Because now people that normally wouldn’t have access to these classes, normally you go to university, you have to pay $5,000 for these classes, you can go take them for relatively nothing or a much cheaper price point online and then still build the same skills. I think it’s just incredible.
Kirill: That’s very true but at the same time do you ever feel oversaturated? Do you ever feel that you’re learning things, new things, but you’re forgetting things that you learned before? Not like immediately before, but you took five courses, now you’re taking a sixth one and you’re forgetting what you learned in the first one. How do you go about that, because I feel that with this availability of education, a lot of people are afraid to go and learn more and more stuff because they kind of know that if you’re not using some knowledge, and in your case, you’re even going out of your way to learn things that are probably not directly related to your role right now? How do you go about retaining that information, and is that something that scares you off from learning more?
Michael: It’s definitely a significant part of the learning process and I think over time certain things get filtered out. But having at least that comfort that you can say, hey, I’ve worked at the tool, I understand the tool, that if I needed to come back to it that ramp up the process or that relearning process to get the cobwebs off is a lot quicker. But to your point, I think it really comes down to what you’re using on a daily basis is really what you’re going to likely be the best at. I think on that same note, that’s really about going deep on things. In collecting different proficiencies and certifications, I’ve tried to keep in mind that while that might serve its purpose, it’s also important to spend enough time with one tool to really go deep on it. That’s something that has motivated me especially with Python and R, two things that I think regardless of the role and the specific software tools you are using, you can apply those to any role and any setting. One of my big mentors, he’s a lead launch engineer at Google, he’s got about 10 years on me and he’s a traditional computer scientist and that’s something that he shared with me and obviously it worked for him, at least from a role perspective. I’ve tried to really keep that in mind, to go deep on topics, not just take one or two courses but like with Python I think I’ve taken six or seven. Then trying to use that on passion projects outside of class or work. That’s really how I think you get good at it, whether it’s a Kaggle competition or a project with friends or other students or colleagues on some interesting problem.
Kirill: Awesome. That’s a great answer, going deep will help you understand the tool much better and retain that knowledge for longer. All right, I’ve got a list of rapid fire questions for you, are you ready for this?
Michael: Yeah, absolutely.
Kirill: What has been the biggest challenge for you ever in this analytics role? Or in this analytics career?
Michael: I would say, piggy-backing off our last conversation, just the amount that you have to learn. I think it’s been twofold for me. It’s inspired me to spend more time with topics and also, it’s definitely a factor that I think maybe scares a lot of people, but I think there’s a natural progression to that learning and it’s also a constant challenge in the right way, it’s like, hey I don’t know how this works but I’m going to figure it out. And I think for me that tooling around is just very inspiring for me, I think data science and analytics is definitely a place for people who are naturally curious, and they want to keep learning and they like challenges, they’re not comfortable just sitting still.
Kirill: Great answer. I love it. The next one is, what is a recent win that you can share with us, that you’ve had in your role? Something that you’re proud of.
Michael: I would say just building trust with the client. There’s a lot of companies out there these days with different software platforms that develop in different languages and I think translating analytics into practice and building trust with the client. Saying hey, based on the questions you asked and the requirements you gather and how you communicate, that’s really the difference sometimes. Given everything else equal, I think people are, by pure market pressure, being called upon to learn a specific set of skills or tools or software development languages, but that trust has been the difference. I’m really proud of that with the current engagement, I think that they have a strong trust in us so that’s huge.
Kirill: That’s awesome. What would your best tip be for building trust?
Michael: I would say listening is key and then asking the right questions. Because when you’ve taken your time before a meeting or an engagement to really prepare and understand the puzzle or the complexities or intricacies of the potential work or the work of that specific client, that will come out in your questions. I think that’s one thing that other people notice- how deeply did you think about the problem at hand? Because these are experts you’re dealing with that often know a lot more detail related to a topic than we do as the consultants, at least initially. But then we come in and we become the experts at showing them how to translate their puzzle or problem into a solution. That initial set of questioning and listening, I think that’s how you build the trust and then it’s wonderful when you sit there, and it clicks with them and they say at the end of the meeting, I really feel that you guys can do this.
Kirill: Okay, that’s a good tip. What would you suggest if somebody is in an engagement as a consultant or even in their own company, and they’re dealing with a person or talking with a person who just has his bias and resists this whole idea that analytics needs to be involved, that somebody has to be helping them sort this problem out? They think they know better and stuff like that. In such problem cases, what would your approach be? Because this is still your client or in the workplace, this is still the person that you’re trying to help, that you need to help in this project. What would your advice be there?
Michael: That’s a great question because I feel like that comes up so often. Regardless of the company I’ve been at over the last five to seven years, there’s always some sort of resistance to change and that’s probably the most difficult thing to break through at clients especially when you’re coming in as a consultant. I think sometimes they might have an industry where consultants are coming in. Practically, I would say I’m showing the value, so almost giving a demo of sorts, whether it’s some certain analysis in R or Python or some other language, or if you have a demo for a related planning puzzle, that speaks volumes. Because what you can do with the client in that regard is give a certain planning scenario that they might have during their day or their 9:00-5:00 and kind of have them work toward a certain success metric manually or as they currently do, which might be manually or semi-manually. But then shown them the power of the solution or the analytics or the tool and how it can add value and make their life easier. Once you show them that you can make their life easier, I think that value really just transcends any sort of biases or walls they might have up. That’s how I’ve seen success getting in with the clients, so to speak.
Kirill: That’s a great way of putting it because, who doesn’t want their work to be easier? Everybody wants that, so I think you’re on to something there. Show them what’s in it for them. Okay, what is your one most favourite thing about being in the space of analytics?
Michael: I would say the constant challenge and that goes hand in hand with all the different methods and tools that are out there. I think the pace of evolution of the field of analytics and data science is just so fast already and it’s just speeding up. Whether we’re talking about machine learning or deep learning or AI, there’s just so much out there that it’s humbling but it’s also so exciting. It feels like you’re on the front of the curve of the normal distribution of the world, you’re part of that group or cohort of individuals that’s an early adopter. For me, I’m a big believer in “moon shots” so being on the forefront of something brand new is really what’s most exciting.
Kirill: Amazing. Yeah, I totally agree. It’s just crazy how things are developing so quickly especially in the world of AI. You never know what’s going to happen in, not even five years, the next year, you don’t know what’s going to come out and it’s always a surprise when it does. Now I’ve got a philosophical one to kind of like wrap things up. I love asking this question because people in different positions have different perspectives based on their experience. From what you’ve seen in the space of analytics and data science and AI, deep learning, where do you think this whole space is going and what should our listeners prepare for to be ready for what’s coming in the future?
Michael: A couple of things. I think not only are a lot of initiatives being set up to have a better impact on the environment, make our lives easier as we talked about, but I think it’s going to get in many ways a lot easier to get involved. I think a lot of companies and different organisations in the tech space are working to make things easier. Like for example with certain machine learning tools or methods where I’ve seen even now, which is quite interesting, some drag and drop type of functionality. I don’t see that importance on understand the science or the coding behind it going away, especially from a statistical analysis perspective, but I think it’s going to get a little bit easier for more people to get involved and then I think once they do get involved, maybe that initial anxiety about learning a software language or learning how to code or learning the math behind a process, will subside a bit. Because they can say, hey I know kind of what the end result is, and I know how to do this now, I’m just going a level deeper, and that can come over time.
Kirill: I like that idea, and especially for some people it might not be necessary to go that deep, right? It could help some people who want to and who will eventually, but it will also enable people who don’t really need that level of depth and that huge level of functionality, but they might benefit from a little bit of extra machine learning in their life. Like maybe, some mum & dad bakery down the road who have no intention of learning R and Python ever in their lives. But if they have that drag and drop tool, even if they get some basic segmentation out of it, some K-means clustering or KMN classification, and if that enables them to run those algorithms just to better service their customers and optimize their products and whatever else they’re doing, that can be a great step forward. I’m pretty excited that you mention this, it does sound like an exciting future, not just for people in data science and analytics, but for everybody in the world in general.
Michael: Yeah, absolutely.
Kirill: All right. Thanks so much for coming on the show, that rounds it up for us. Where can our listeners contact you or follow you to see what are the next things you’ll learn, which countries you’re going to visit, and how your career is going to progress from here?
Michael: I would say the best way is just to contact me via LinkedIn. My last name’s a little bit hard to spell, COLELLA, but you can find me there and I’m sure my last name will be in the show notes as well. LinkedIn is the best and also on Twitter, I’m trying to build more of a social media presence, but I can be found on Twitter as well.
Kirill: Awesome. Great, that will definitely be in the show notes. So you guys, hit up Michael on LinkedIn and follow him on Twitter. And one last question for you today. What is a book you can recommend to our listeners to help them become better at what they do?
Michael: I would say, again, the technical proficiencies are important but there is a book that’s been extremely helpful for me, it’s called 60 Seconds And You’re Hired! by Robin Ryan, and it really focuses on the communication aspect of business or interacting with clients, or just getting a job in data science and analytics. I think that’s a way to show beyond all of the different technical tools that you might have or languages you might know or methods you might know. Showing your future employer, or the people you’re interacting with can be comfortable that you can actually talk about what you’re doing. I’m just thinking by default when you’re giving a presentation or a data visualization, having that ability to communicate in literally 60 seconds or less, the value, I think that speaks volumes.
Kirill: I think that’s a great suggestion. I haven’t read that book myself, but I think that would even be beneficial for people who are in the space of entrepreneurship or figuring out ways to use data science to help other companies as consultants or if they need investors because 60 seconds can be an interview thing, but it also could be an elevator pitch and maybe that could be useful there. Thanks for the suggestion, the book’s called 60 Seconds And You’re Hired! by Robin Ryan. All right, Michael, thank you again so much for coming on the show and spending some time with us here today, we really appreciate all the insights and the amazing story. I hope you have a lot more consulting fun engagements in the coming future.
Michael: Thank you so much, Kirill. That was a real pleasure.
Kirill: There you have it. That was Michael Colella and I hope you picked up some very powerful insights from this conversation. Personally, I got two main takeaways. I usually mention just one but this time I think it’s important to mention both of the takeaways because I feel they’re important. Lots of things but the two main ones. Big takeaway number one: Michael was passionate about travel and he knew that he was passionate about travel and he managed to incorporate that into his career. Not just managed, he set out to find a career that incorporated travel in itself as a major component of the work. I find that very admirable, that he didn’t let go of his passion, he didn’t sacrifice, he didn’t trade it in for a big pay check or just interesting work like sometimes you might think, if I want to do this work, I can’t do what I’m passionate about. But that’s not true as you can see from Michael’s example, he managed to incorporate that, his passion into his work. He built himself a career where he travels and does analytics, and he does data science. That’s big takeaway number one. By the way, from the previous podcast, where we were talking with Eric, he managed to do the same thing. He is passionate about education and he incorporated education into his career. There you go, those are two examples and it just stands to show that whatever you’re passionate about, whether it’s helping other people, saving the planet, helping animals, nature, physics research, whatever it is, there is a way to incorporate it into your career as a data scientist. That’s number one.
And takeaway number two is that I really liked how he described how he took a pause to go to Brazil and teach English to children there for three months and how that was intentional to help him realign in his own life, understand what he wants from his career and what he wants from his future, what he wants for himself. Because a lot of times in life we get caught up in the moment, get caught up in all these minutiae of life, and all these things happening around us, like Michael said, he put it very aptly, as soon as he got back, people expected him to be online. We have expectations that we have to conform. These expectations are of other people and we sometimes don’t even know what we want ourselves, and I think it’s very important to know what we want and if what it takes is to go to Brazil for three months and disconnect and just find yourself there, then that needs to be done. I really respect Michael for having the courage to do that and for actually going through with it. I think that a lot of people in this world could really benefit from that and have much happier, more fulfilled lives if they truly knew what they want for their own lives. I personally think I’m going to take that advice on board and hopefully one day I’ll be able to … It’s all up to all of us, I’m already making excuses, but one day I’m going to do something similar and disconnect. Maybe it’s something that needs to be done regularly, maybe every couple of years you need to go away and just find yourself. That was a very cool excurse into a part of his life.
There we go, that was Michael Colella. You can get the show notes for this episode at www.www.superdatascience.com/113, there you’ll find the transcript for the episode and all of the materials that we mentioned and plus you will get the URL for Michael’s LinkedIn and his Twitter. Make sure to hit him up and connect on LinkedIn and follow him on Twitter. Help a fellow data scientist build out his social presence, as he said he is building out his social presence on Twitter, let’s help him out. On that note, hope you enjoyed today’s podcast can’t wait to see you back here next time. We’re slowly getting close to the end of the year, only a couple of weeks left to go, and I look forward to seeing you back here and until next time, happy analysing.
