Can you introduce yourself and tell us a bit about yourself and your background?
I’m Sarah and I’m in Brussels for about 3 years now – still it feels like I’m super new here. Originally, I’m from Germany, the Saarland region to be precise, from a little village in the middle of nowhere. I’m 34 years old, but on average currently it’s 17 only, given the little kicker in my belly.
What is your job and what does a typical day look like for you?
When moving to Brussels, I joined Sirris, the collective centre of the Belgian technological industry as a Data Scientist. In the bigger picture, we do perform applied research with Belgian partner companies, research centers and universities to drive innovation. And that means that during a typical work day, I spend time on different projects, with different partners in (too many online) meetings or if I’m lucky, I can code for a while without interruption, before writing together with my colleagues project proposals, … So as with so many jobs: Typical is hard to define.
Can you tell us a bit more about the kind of projects you get to work on at Sirris and what that entails for a senior data scientist?
The projects we mainly work on are in applied research projects together with companies. We’re somewhat between universities and industry, with the aim to go beyond the state of the art while still working on real-world data. That is what triggered me most when joining: How can we build ML and AI solutions that are actually useful for companies, in real applications. That of course also means staying up to date with respect to academic research, reading and writing scientific papers etc.
Which phase(s) of a project are you involved in the most?
All of them 😁 From proposal writing, to requirements discussions, to hands-on coding and project management and (final) reporting.
Which is the favourite part of your job?
The thinking part. I love it that I have to think a lot every day during working hours.
How about when you’re not working? Any hobbies or interests you’d like to tell us about?
Here in Brussels I learnt that I’m very German: One of the first things I did was joining a choir. Together with about 30 others Germans as it seems. 😉
What kind of songs does your choir sing?
From baroque student drinking songs to the Beatles. Our repertoire is very broad.
What or who got you initially interested in coding and / or pursuing a career in tech?
It was a bit by chance: I studied physics and only at university I started coding, which I didn’t expect. I ended up in statistical physics, which is related to many particle systems and often, you can only approximate solutions with numerical methods. And that is how I figured out that I actually quite like it. Seeing my code from that time though gives me shivers nowadays!
If you look back on when you first started out. What advice would you give yourself?
Be patient. Coding needs time and practice. And listen to others when they say: Give your variables meaningful names and write documentation. You never know when you need this small snippet of code again.
Are there any particular women in tech who have inspired you?
Two actually, but mainly by working with them: Cecile Appert-Rolland, one of my two PhD advisors and Elena Tsiporkova, my current boss.
Do you have any favourite resources or projects you like to follow?
I do really like algorithmwatch, to keep the ethical side in focus. For more coding related things, Jason Brownlee is doing a great job.
What are your thoughts regarding the fast advancement of technologies such as AI in terms of ethics and/or ecological impact?
It needs regulation. Not on the algorithm level but I’m very much in favour of some kind of certification for applications that influence our lives and that are trained on personal data. Or applications that can strongly influence society, like deep-fake videos and fake news stories. Societies are too fragile for a bunch of lies.
And the never-ending growth of models (and hence their training time) isn’t helpful either. It’s one of our focus points: finding models that do the job but are as small and by that as eco-friendly as possible.
Do you have any thoughts on how we could prevent the misuse of technology?
When it comes to deep fakes or fake news stories: I have no idea. I don’t see a smart way on how to prove that something is real or not.
When it comes to the misuse of personal data, I think that creating awareness is very important. What happens with the data you’re sharing? How do your cookies influence your search results? This can be done by campaigns.
Plus, regulation. We saw it with GDPR, how things started to change worldwide. I hope that the AI Act has a similar effect.
If someone wanted to move into a career in data science, what would you advise them? Where should they start?
I think there are many different ways. Some people I know rather come from the mathematical side and learn coding, while the others more come from the software side and learn the data modelling and math. So it does depend on your starting point. Luckily, in Belgium are quite some networks and meetups on the topic. Go there, meet people and get in touch. Most people there will for sure try to help you.
As a woman in tech what (soft) skill/trait do you find the most useful/crucial ? What advice would you give in order to learn it? (Question from Sarra L)
During my work, I see that it’s very useful to listen and stay calm. Some women try to mimic “classical male characteristics” but I don’t think that it’s helpful. As in every team, the diversity is what makes the team better.
What made you join the women.code(be) community?
I love the exchange with other women in the field and I believe that it’s super important to have networks for women as well, to recommend each other for possibilities and push names.
How could the tech industry be more inclusive for women and minorities?
I think we need to start early, in school. Not necessarily with coding, but in how to overcome this gender stereotypes such that girls are not afraid of maths etc.
Do you believe that AI will also enforce the stereotypes that have been propelled at us by media sources, but also by our society as a whole?
Absolutely. It’s all it knows. AI can only learn from what is already here and that data is highly biased.
Little experiment: Ask ChatGPT for ideas for a 4 year old girl for her birthday and a 4 year old boy for his birthday.
First idea for a girl: Doll or stuffed animal.
First idea for boys: Toy Cars or Trucks. What else shall I say…?
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