Alumni Spotlight: Willem Zents on social data science

Willem graduating from Oxford

Name: Willem Zents

Year: 2019

Major: GED 

Currently: Analyst at Bumble

Athéna: Today we’re sitting with Willem who graduated in 2019 in GED and will take some time to reflect on his journey. So what have you been up to since you graduated? 

Willem: After I graduated, I interned at NIBC Bank, a corporate and investment bank. I then joined a company called Picnic, an online grocery store. It is much bigger now than when I first joined. The scale up phase was exciting, loads of young people worked there and the atmosphere was informal. I was in an analytics role in the commercial team, doing all kinds of data analysis on the commercial side of things. This was mostly related to things like which products are we going to have in the store, how to price them, promotional strategies, working with some cool brands, learning about food trends etc.

After this, I decided to do my master’s in data science at the University of Oxford. This was quite an adventure, especially with the ongoing pandemic at the same time. My master’s were in social data science, so computer and data science methods applied to social research and policy questions. A big part of it was looking at fairness, accountability and transparency in artificial intelligence and data ethics. Thinking about how digital technologies affect our daily life such as dating apps. An example is how dating apps influence the way that we see relationships. Do they make it easier or more difficult to meet? These kinds of questions. So overall, studying in Oxford was amazing, from the unreal facilities to my really nice classmates.

Then, I wanted to move to London. It is a good place to be young I think, and I wanted to be in a role that was a bit more related to aspects I looked at during my master’s, such as online safety and technology. I then found this really cool role in analytics at Bumble, a dating app. I focus on the safety side of the app, making sure that people have a safe and enjoyable time using the app chatting to people. There is all kinds of unsafe behaviour on dating apps such as people sending rude or unsolicited sexual messages. Some people have a more difficult time meeting people on dating apps like trans people or non-binary people who don’t necessarily fit into the binary notion of gender that much of our society is based on. So there are a lot of challenges there to make sure we can all have equitable, healthy and fun relationships.

Willem working for Bumble

Athéna: You mentioned that your current job is about ensuring online self-safety and touches upon the ethics of technology. What does that practically involve in your work? 

Willem: For Bumble, safety is a core part of what we do. Basically, I am a data analyst, we have lots of machine learning models running. For example, if someone sends a message to another user, then there is a model that sort of goes through that message and checks that it’s not offensive, rude or harmful. It also checks if the person is not trying to sell something illegal on the app, such as Premium Snapchat or Onlyfans accounts.

I work with the engineering team that makes those algorithms on the one hand, and on the other hand the product teams or product managers who are in charge of the features the app has. For instance, if we tweak the algorithm to make it a bit more sensitive to these things, what does it do to the way that users use the app? So if we add a new feature to the app i.e. a new button that users can use to report unsafe behaviour, then we analyse how people are using that feature. Is it leading to more reports? Are the reports that we’re receiving accurate ?

Athéna: You must have a quite strong background in programming to interact with engineers as well as product managers. Is this something that you acquired in your master’s or through your internship?

Willem: I was never really thinking about programming as much when I was 18, until we started doing statistics in our first year at LUC. Doing those kinds of analysis with a programming language like R sort of opened up a world to me and made me curious to learn a bit more other programming languages like Java and Python,and I ended up really enjoying it. In my third year, I decided to do a minor at a different university and went to Erasmus University in Rotterdam to do a computer science course.

It was really nice to learn some hard skills which are needed to become a good programmer like linear algebra, relational calculus, the kinds of things that you don’t learn at LUC, but are pretty important unfortunately to pivot a bit into the world of data science. I actually didn’t really do much programming at all there, it was mostly solving equations, but that gave me a good mathematical background. This meant I could signal to employers on my CV that I had done computer science and request an internship in data science or data analytics. That’s how I landed up my internships.

During the internships at NBIC and Picnic, I learned a lot of practical stuff about what it is like to do analytics in a company with real world data. My master’s program builds further upon that knowledge with things like machine learning and the more advanced parts of data science. So it all started with doing an external minor in computer science while I was initially underqualified, it was a third year course and most of the other students either had done maths or econometrics. I was really struggling to deal with the math, but I pushed myself through. So it wasn’t a really enjoyable experience necessarily, but it’s just kind of a rite of passage that you have to go through.

Athéna: What would you say are the main skills needed to jump into data science?

Willem: My master’s program was in social data science, I think they were really looking for people who had both: solid data science skills, a good level of commands of a programming language, an analytical mindset , but then also they wanted people with a good understanding of social science or social science research methods. It’s not about using data science for business per se, but looking at how it can be applied to social phenomena. 

Data science doesn’t equal tech skills. There are so many roles that are not technical such as user experience research and UI design, which are very interesting and don’t usually require any technical skills. There are lots of policy roles, so we have lots of people working at Bumble who studied gender studies or LGBTQ+ studies, for example working on member’s safety policies. Not having a technical background is not a problem. 

Athéna: You mentioned that through your first internship, you realized that this environment wasn’t for you even if it was data science related, it was lacking a social dimension. What didn’t you like about your first experience and why is social data science more interesting to you? 

Willem: The first bank I interned at was an older company, with a lot of regulations and overall a very different atmosphere. People were working there for 20 years, and were in a completely different life phase than me.

Willem working at NIBC

When I then joined Picnic, it was more fun and stimulating overall. What I like about analytics and data science is that you can really answer questions and gain new knowledge. For example, a product manager will be like: “hey, I want us to explore how the pandemic has changed the way people look for a romantic partner.” That’s a question that you know you would have no idea how to answer, and you know that knowledge doesn’t really exist yet. By using innovative methods you can dive into data and extract valuable insights. These insights can feed back into a product that you are building like an app and you know it has an added value. Once you provide the insights, there’s a big part of how to translate your findings into a data story and I find this process very stimulating.

Athéna: So from your experience, when people look for jobs they should check if the culture of the organization matches their values but also what they are interested to focus on specifically in terms of topics?

Willem: 100%, those two things are crucial.

First of all, if you’re going to work in data science, you’re going to be working with data on a specific topic all the time. So it really matters if it’s like something that you personally find interesting. You’re going to be doing a lot of work on this topic, so you better enjoy it.

Secondly, your work environment is crucial, because you spend most of your time at the office surrounded by your colleagues. You have to think about whether you are surrounded by people who inspire you, lift you up and make you happy, rather than people who do their own thing and that you don’t really have a connection with.

You can research these two things in advance. When getting into a new workplace, I would advise to make sure that there are also other people of your age in that company. You may have a very difficult time levelling with someone who is 45 or 50.

Athéna: What are other factors you would consider important when applying for a job?

Willem: I chose Bumble also because of two things that I consider important. Firstly, their approach to mental health. They have a really strong emphasis on work-life balance and they give you a lot of support in terms of mental health resources and making sure that you don’t burn yourself out. There’s unlimited personal time off and they do these focus Fridays every other week, where you can just focus on your own work or your own projects without getting distracted by meetings and emails.

I think a company that keeps an eye out for work-life balance and makes sure that their employees are thriving in their own way, especially at a technology company, is important. There are lots of really big tech companies that I think have a lot of power that they could be using in very different ways than they are doing right now. We can all think of tech giants that wield so much influence and often I find it a bit disappointing how they deal with work-life balance and mental health.

Secondly, I really look for companies that keep an eye out for the impact of their products, who does it impact and how, making sure that the impact is fair and inclusive. 

Willem holding his LUC thesis

Athéna: To wrap up our conversation, looking back on everything you’ve done, from your minor that was a big turning point in your life to the internship experiences you had, and finally your master’s and current work at Bumble, what would be a life advice that you would give to recent graduates and alumni? 

Willem: I get a lot of questions on how to get into data science. I think the nice thing about a LUC degree is that it’s virtually limitless, you can do pretty much anything you want with it if you put the work in a certain direction. It is vague and sometimes people don’t understand it, but I would definitely say: use that to your advantage and don’t be afraid to, as I did, jump into a topic if it interests you. Whether it’s through an external course, learning a programming language, following an online course to build your skills and then use the combination of that in your degree to sort of present yourself as an interdisciplinary thinker. Your background is unique. So if you can supplement your background with a little bit of hard skills that you’re eventually going to need, then you’re good.

Athéna: As you mentioned through the conversation, there are also other data related jobs that are not necessarily data scientists, like product managers. Since you’re going to be dealing with data analysis most of the time, even if data scientist sounds interesting, make sure that you actually enjoy the process itself, like you do. If you don’t really enjoy programming etc you could be wasting your time.

This concludes our interview, thank you again for taking the time to share your story with us. If people are interested in Willem’s journey, don’t hesitate to reach out to him!

This post was part of a larger series of “portraits” of Alumni. Want to be featured, have questions for Willem, or about alumni in general?
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