Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.

[00:00:00] Dr Genevieve Hayes: Hello and welcome to Value Driven Data Science, the podcast that helps data scientists transform their technical expertise into tangible business value, career autonomy, and financial reward. I'm Dr. Genevieve Hayes, and today I'm joined by Sayli Javadekar. Sayli is a data scientist at ThoughtWorks with experience at the World Bank and UN aids.
[00:00:28] Before this. She was an assistant professor at the University of Bath and holds a PhD in econometrics from the University of Geneva. In this episode, we'll discover some of the key challenges data scientists face when transitioning from academia to working in industry and discuss practical strategies to help data scientists develop the business acumen needed to succeed.
[00:00:55] So get ready to boost your impact, earn what you're worth, and rewrite your career algorithm. Sayli, welcome to the show.
[00:01:03] Dr Sayli Javadekar: Thank you for having me. And thank you very much for the very kind introduction.
[00:01:08] Dr Genevieve Hayes: Until I was almost 29, I'd only worked for a total of one year outside of the university world. My first proper job was as a university teaching assistant, and while I was completing my PhD, I worked full-time as a university lecturer. So when I started applying for jobs outside of the university at the end of my PhD, I remember being shocked by some of the negative attitudes towards academics.
[00:01:35] I observed in some of my job interviews, I'd enrolled in my PhD. Believing the qualification would make me seem more valuable to prospective employers, but it seemed like the reality was that it made me appear less so, and I didn't understand why. That is until I started my first post PhD role and realized that despite my PhD equipping me with theoretical skills that were more advanced than those of many of my coworkers, I was also behind them in many ways.
[00:02:10] The learning curve in my first year was brutal. As any data scientist who's made the leap from academia to industry would agree. Making this transition isn't just another career change. It involves a complete shift in the way you work. And unsurprisingly, at first, it can be a pretty big struggle. Now, more than a decade has passed since I left academia, and I'm pleased to say I survived.
[00:02:40] But Sayli you've made this journey far more recently. To begin with, can you start by telling us a little about your academic background and what made you decide to leave academia and go into industry?
[00:02:54] Dr Sayli Javadekar: Yeah, definitely. So I'm trained as an economist. I did my PhD in Geneva. I worked on issues in development, labor, and applied. At econometrics. After my PhD I decided to, stay in academia and go for an academic position. So I did end up with a tenure track academic position in the uk.
[00:03:15] It was a dream come true. That's literally what every PhD student wants. And I got it. I was there for about three years and it was going quite great. However, I think this was perhaps. Around the time when COVID hit and I got a bit disillusioned by academia because when I started with economics, my motivation was that it would ultimately create some sort of impact.
[00:03:44] But I didn't see that happening. I didn't see my research translating into something that will actually matter. It just felt like, you know, I want to publish papers and I want to build my own ego in a way and just make myself feel more intelligent and more important by publishing more.
[00:04:03] It didn't feel like any of the work I was doing really, helped anyone's life. Get better. So it was around that time when the solution mentors started setting in, I was also working with a lot of international organizations and working a little closely with them. I also realized how the incentives of different players are quite misplaced and despite these being large scale international organizations, I didn't feel they ultimately cared for.
[00:04:34] Making an impact. I mean their jobs, of course, really stated that they wanted to make an impact, but it didn't really feel like at the ground level something was changing. Along with that with every academic position, if you want to change something, you have to move cities, rebuild your life from scratch in a different city.
[00:04:54] There was certain times in life I felt that in my chase towards this academic dream, I had left my personal lives behind. And also being an immigrant, I had to go through the entire. Hurdle of applying for visas or not being able to travel a lot, easily to meet my partner who at the time was in Germany.
[00:05:14] And I was stuck in the UK and it was quite difficult for us to meet. So there were multiple things that came in together. The personal life that was a bit in shambles, the professional life that didn't live up to the mark. And therefore around that time I thought that I needed to change something.
[00:05:31] And I had spoken to a few other seniors from my PhD who also had transitioned out of their tenure track positions to industry jobs. And after talking to them, I realized that perhaps this was a shift that I also would like to make. So last year in January, 2024 I left my academic job. I moved to Germany and tried to rebuild this new thing from scratch.
[00:06:00] It wasn't a very easy transition because as you rightly mentioned, a lot of people in the industry do not have. A clue about what academics do, and rightly so academics have not done a very good job in communicating with them. And in academia we have no idea how industry functions or what are the things that matter to them.
[00:06:25] So it was quite a tough transition. The first struggle was to find a job and to convince the industry folks, the recruiters, the, first people who are going to interview you, that you can actually do the job or if not the job.
[00:06:39] Exactly. You have the skills to build, new skills to do the job. What helped me during that time was to reach out to people on LinkedIn. I used to send a lot of cold messages to people asking them about their transitions asking them for a call asking them to refer me. And I must have applied to over 200 positions and I ended up with three interviews.
[00:07:03] Out of which ThoughtWorks was the only position that I ended up receiving an offer for. But all, the three interviews that I received were through reference. That's another thing that academics have no idea about that in industry things happen or you can get an interview through referrals and you can reach out to people and ask them for referrals.
[00:07:23] So that was something that I discovered. Since joining ThoughtWorks, also, it has not been a very easy first year. It's been about a year now for me at ThoughtWorks. There has been a major mindset shift that is required of me. Initially in research, we really work because we are so motivated about a particular topic in the industry, you really have to work
[00:07:50] to improve certain business KPIs and that is what matters. Things have to be much faster in the industry. They have to be delivered much faster. The hard work that you put in does not matter if there's no value that's created out of it. So there has been a bit of a mindset shift that I had to make and I think I still am learning and making that mindset shift. The other difference I realized was the speed at which things move in the industry.
[00:08:17] It's so much faster than in academia. That is something I'm still learning and trying to keep up with. So those were the two major struggles for me in the first year and throughout the transition.
[00:08:30] Dr Genevieve Hayes: As you're speaking there, so many of the things that you were describing were things that I'd also experienced when I made that transition. Part of the reason behind me wanting to leave academia was because I'd just finished my PhD and. I'd spent four years on this piece of research and nobody seemed to care and to me, it was a big deal.
[00:08:53] So I thought, why doesn't everyone else care about this? And I remember, it was all about coming up with an alternative to the capital adequacy requirements for life insurers. And I look back on this and I realize how naive I was at the time, but I had not had any contact with the regulator during my PhD.
[00:09:16] What I did was I spent four years doing the thesis and then emailed a copy of my thesis to the regulator afterwards, and they didn't even send me an acknowledgement of it. And, and I remember thinking, but, but, but I've come off with an alternative for your regulations that are so much better than what you have.
[00:09:37] And, it's laughable now, but at the time I didn't understand how things worked and. Yeah. And that was something that led me to leaving. And also many of the challenges you're describing in particular the speed at which things work.
[00:09:56] One of the things I found was after going from spending, four years on one major project, it really messed with me having to juggle, half a dozen projects all at once. And I remember being on the phone to my parents and complaining about this, and my dad was explaining to me, no, that's how things work in the real world.
[00:10:18] You just gotta deal with it.
[00:10:20] Dr Sayli Javadekar: Yeah, but I think it can be quite overwhelming to someone coming from academia who is just used to working on one piece of work for a long, long time and sort of perfecting it to the T, and now you have to transition to a place where you just want a good enough. Or a good enough piece of work and that needs to be delivered and then you move ahead.
[00:10:41] Yeah. So that is a bit of a mindset shift.
[00:10:44] Dr Genevieve Hayes: Yeah. Where. All your academic training left you least prepared for the industry work.
[00:10:49] Dr Sayli Javadekar: I think in a couple of places first of all. In academia, because you've spent so much time there, you really feel that you're very smart and that you know better than everyone else. I think that's one thing that coming to industry, I realized that there are a lot of things that I have to still learn.
[00:11:10] Just because I have a PhD does not mean I know everything. I think that was one sort of to adapt to have the beginner mindset again. So I think that is. Maybe something that I don't know how to describe it, but it feels like in academia we are all on high horses where we sort of think that we are superior or we do something better than the industry folks.
[00:11:33] That's perhaps not a very good sort of way of approaching things. Every piece of work is important and everyone works hard. Academics are not working harder than regular folks in the industry or vice versa.
[00:11:46] So that's perhaps one thing that I thought academia left me with. Sort of The superiority complex. The other thing I think, we are very slow at adapting to new technologies. As an economist, I worked a lot with data and an r. However there are great technologies or great languages like Python.
[00:12:06] I never worked with Python or cloud technologies. I had no clue about cloud technologies. So those are new things. GitHub was the third thing that I never worked with before. So perhaps these are the new tools that could be very useful for academics as well. But we are not trained in that thirdly, we do not really understand how business folks think, what matters to them. What are the KPIs that need to be improved or what can be changed. That is another thing that I thought that academia never really trained me for. Sort of understanding how the industry functions and what are the incentives of different agents or different players in that game.
[00:12:56] So these are the three major things that academia didn't really train me for.
[00:13:02] Dr Genevieve Hayes: For me, I found the business style of communication was something that I really struggled with, so one of the things that happened shortly after I left academia was my boss asked me to draft an email for him to send to his boss, and I was so used to that really formal academic way of communicating where, you have to clearly state all of your evidence and how you connect from point A to B2C. And so I wrote this. Beautifully written, well justified email for him to send to his boss. And he CC'd me in on what he actually sent. And his version was along the lines of, Hey mate, here's the outcome we reached, cheers. And that was not at all what I'd written. And I just remember being so embarrassed by what mine looked like compared to his.
[00:14:01] Dr Sayli Javadekar: Yeah, that's true actually. That really reminds me that that is another thing that I do struggle with the language of consulting. I come across as maybe too direct. And that can come off as very rude, and it's not diplomatic and there are certain things you don't see to certain people.
[00:14:17] So that's another thing that I'm struggling with or something that I acting never really trained me for how to communicate with people.
[00:14:25] Dr Genevieve Hayes: So have you reached the point where you feel like you're starting to get the hang of being an industry data scientist yet?
[00:14:33] Dr Sayli Javadekar: There are days when I do feel that I am understanding what is going on, but then there are other days when I'm confused. But then those days, I think I reach out to a mentor or a colleague. Who will then bring me on track? So I wouldn't say completely there.
[00:14:49] It's just been a year for me in the industry, so I'm also trying to be kind to myself and keep telling myself that it will slowly come to me. And as it was also during my PhD, it did take time to get a hang of research in the same way. Being an industry data scientist, it will eventually come to me. I do feel I'm closer to it now than I was a year back.
[00:15:15] Dr Genevieve Hayes: What strategies or approaches have you found most helpful in bridging that gap between academic and business expectations?
[00:15:23] Dr Sayli Javadekar: There are a couple of things, but the one thing that completely stands out is having a mentor in the company because they are the people I can reach out to if I have any questions. And I think that they don't judge me, so the question can be as. Stupid as I may think it is, or it could be a relevant question, but it's something that I don't understand.
[00:15:44] So having a mentor I think is so important. Having someone to reach out to, to discuss different dynamics and to understand how the industry functions. The other thing I have also realized along the journey I've had is how to communicate, findings in a businessy way rather than just providing them with statistical measures.
[00:16:08] Something that I think stood out for me even during my first gig within ThoughtWorks was I was very naive. I told the client certain statistical measures that I had found, and at the end of it, the client was like, yeah, but what does it matter to me? Does it improve my KPI or not?
[00:16:27] And at that point, I did not have an answer. And that's when I realized that it doesn't matter to give them, a statistical measure, what matters to them is, does it have a positive impact on their business? So that's one thing I've learned that I need to communicate. My findings in business language.
[00:16:45] The other thing I'm learning and I have also realized is important, is to prioritize just a minimum viable product rather than going for the perfect solution. So. Fail fast.
[00:17:00] That's a mindset that I'm adapting, that even if it's something I want to try, I should try it. And it's okay if I fail, sort of the bias for action fail. It's fine. You know, it's not working, you move ahead. So I think that's the other sort of strategy or the prioritization of things. And of course something that, has helped me a lot and is still constantly helping me, is to keep upskilling. So Python is relatively new to me and I. Use now AI a lot to help with coding and to learn new things in Python, to learn about different cloud technologies to learn about other machine learning models through courses or through blogs.
[00:17:43] I think that's the third thing that has helped with this transition out of academia to sustain in the industry.
[00:17:51] Dr Genevieve Hayes: I would agree with your comments about the importance of having a mentor. I was very lucky. The managerial role that I had shortly after leaving academia the woman who'd previously held it was about to retire, and she was sort of in a transition period, so they were paying her to keep going with the job.
[00:18:12] Until I got up to speed on it. So she acted as a mentor towards me and she was excellent. And she was, very kind. She wasn't going onto the next big job. Her next thing was, spending her days on beaches with her feet up. I dunno, whatever. But that really made a huge difference for me.
[00:18:34] Dr Sayli Javadekar: Yeah, I think amenta is so important. I mean also in research we had a PhD supervisor, right? The PhD supervisor. They were the ones who I. Did us through the process. So similarly, I think in industry it is important to have someone you can reach out to who you can talk to about the questions you have or the problems you're facing.
[00:18:53] So yeah, I think mentorship is a very underrated skill.
[00:18:56] Dr Genevieve Hayes: Yeah. The other thing that really helped me was volunteering for. Various projects that put me in a group with other people who weren't data scientists, because that exposed me to a lot of other areas of the business, and that allowed me to see things that I hadn't previously experienced and learned from that.
[00:19:19] Dr Sayli Javadekar: That's very interesting. That's something I've not experienced so far, but that's something I would really like to go for because it allows you to get a holistic understanding of how the, the entire business functions, right.
[00:19:31] Dr Genevieve Hayes: Yeah, and like for example, one of the things I did we had a policy team, so it was. Basically a team of lawyers and I volunteered to help my boss recruit for a graduate who was gonna be within that team. And so it involved, looking at all the resumes for people in that area and understanding that area in order to help her select someone.
[00:19:55] And that just helped me to understand, oh, this is what this area of the business does. You know, just little things like that.
[00:20:03] Dr Sayli Javadekar: But I think what stands out. Is having a very open mindset and having a very open attitude to learning different things. So rather than being very rigid about, oh, this is what I work on and this is what I'll be working with and not, I, do not want to look at anything else. I think that's,
[00:20:21] such a good point.
[00:20:23] Dr Genevieve Hayes: Yes. So if you could go back in time to before you left academia, is there anything you would've done differently to make your transition to industry easier for yourself?
[00:20:34] Dr Sayli Javadekar: Yes, definitely a few things. So one of the things for sure is. Something I struggle with is coding. So I think that's something I would definitely take up and do a lot more of. I practice a lot of the stuff that I worked on in state or in R that could be done in Python. Given that, in industry, everyone, we just working with Python, I think that's one thing that I would've definitely worked a lot on.
[00:21:02] Secondly, I think I should have taken some sort of a business class at the university just to understand how it works outside of my little bubble of econ, academia. So maybe a business class would've really helped. Or a leadership lesson or some sort of a non-academic communication lesson.
[00:21:22] So maybe that's something I should have invested in.
[00:21:27] Dr Genevieve Hayes: I think if I could go back in time, I would've done more networking with non-academics.
[00:21:32] Dr Sayli Javadekar: Are we. Definitely. Yes. Yes, yes, definitely. Yeah, that's a very good point. And that actually reminds me this could be another thing that I should have done is an internship. I should have interned during my PhD in the industry just to understand how the industry functions because it's so much different than what I theoretically understood about industry before I left.
[00:21:56] It would've been very useful to intern somewhere.
[00:21:58] Dr Genevieve Hayes: Yeah, I would agree with that. Yeah. If someone listening is currently struggling through making the transition from academia to industry, what's one thing they could start doing tomorrow to make their life easier?
[00:22:11] Dr Sayli Javadekar: I think one of the things definitely is to reach out to people on LinkedIn or on Twitter or ex now. The people who have transitioned, who've had similar journeys perhaps in your own field because you can relate to them better ask them about their transition. However, everyone's journey is also very different, and so their journey may not necessarily reflect your journey.
[00:22:36] But you get a general idea of the things that are required or the things that you may possibly face. The other thing is most definitely, if you can in turn, in the industry, spent two months, three months of how much of amount of time you can. That would really give you a firsthand experience on how the industry functions and whether you like it or not.
[00:22:59] And then you can make a more informed decision whether you want to leave that team or not. So I think that's definitely something I would recommend.
[00:23:07] Dr Genevieve Hayes: So for listeners who wanna get in contact with you s what can they do?
[00:23:12] Dr Sayli Javadekar: So I'm very active on LinkedIn so they can reach out to me on LinkedIn. Feel free to send me a message. And I'm very happy to get in touch with folks who are in a similar journey transitioning out of academia or want to just talk about books or painting or, life in Europe. And I would be very happy to reply to them.
[00:23:32] Dr Genevieve Hayes: And there you have it. Another value packed episode to help turn your data skills into serious clout, cash, and career freedom. If you enjoyed this episode, why not make it a double? Next week? Catch Sayli's value boost a 10 minute episode where she shares one powerful tip for getting real results real fast.
[00:23:54] Make sure you're subscribed so you don't miss it. Thanks for joining me today, Sayli.
[00:23:58] Dr Sayli Javadekar: Thank you for having me. Have a lovely day.
[00:24:01] Dr Genevieve Hayes: And for those in the audience, thanks for listening. I'm Dr. Genevieve Hayes, and this has been Value-Driven Data Science.