Before moving into data science, I was a researcher in Physics. During my PhD, I focussed on neutrino astrophysics and was part of the international collaboration of scientists who built the Antarctic neutrino telescope IceCube. Later on, I searched for dark matter at the Gran Sasso underground lab in Italy.
On the way, I acquired a lot of knowledge that I no longer use today – like applying Noether’s theorem and the nicknames of our detector’s most capricious sensors.
I also learned some hard skills that are relevant for the work I do today: The data I used in my research didn’t fit in a spreadsheet and the signal I was looking for was tiny compared to the noise we collected. To complete my research, I improved my programming skills and studied statistics. I became expert in A/B testing and developed a scientific mindset.
But even more than those skills, I value the attitudes and habits that doing a PhD in Physics taught me:
One of my earliest research presentations contained a figure with data that had a structure that I had not even noticed – I was way too focussed on the conclusion I wanted to support with it.
On that day, I learned that showing data with features I do not fully understand to a room full of physicists – or anyone who works a lot with data – does not help to win their trust.
Over time, I developed a habit to confirm that every step in my data processing behaves as intended and expected, and to make sure I understand all the major features and trends in the data I work with. As a lead, I question and validate the assumptions I use to make decisions.
Courage to speak up
As a researcher I was lucky to work in environments where most people valued insight more than hierarchy. My supervisors encouraged me to speak up and disagree with them and others – often professors from other universities – when I had a point to make.
With practice, I became confident to contradict others when I thought they were missing something important. Doing a PhD in Physics taught me to speak up in public (like at conferences) and to folks with higher status in organization than myself.
Confidence in my ability to learn
Getting a Physics degree involves going through a lot of formal training. But the further I progressed, the more often I had to acquire skillls and knowledge on my own to move forward.
For example, our professor’s approach to teaching programming was to simply give us a task and a deadline. I am old enough that back then, we couldn’t just find the solution on the internet. We were actually stuck with the task, and solving it meant to go and figure out how to learn programming first.
As a scientist, I often worked with tools, algorithms and methods neither my supervisor nor anyone around me had worked with before. While that was sometimes hard and frustrating, it helped me see that with perseverance, I was able to learn whatever ws needed to progress, even when it was challenging and complex.