From Physics to Data Science: The Story of an Asigmo Fellow
Asigmo: Please introduce yourself:)
Diana: My name is Diana, I am a Colombian physicist (for almost 11 years now!) and a data scientist. I did my Ph.D. in Brazil and then moved to France where I am currently based.
Asigmo: Why did you decide as a physicist to become a data scientist?
Diana: I have always been fascinated by how you can get insights about the future through the patterns in data, and finding these patterns is something that I have been doing almost all my life! so become a data scientist was natural for me: coming from a physics background, all you need to do is to solve a problem: You have the mass and the gravity, and you want to know its velocity, or you would like to know what happens when you throw something and in both examples is essential to keep in mind the ‘what is the main goal?’, ‘what do I need to solve?’ and ‘what tools do I have?’ to solve them. In data science, all these questions are back, and I will add an extra point here related to the limited time you have to solve the question, and this is why is really important to stay focused on what is what you need to answer. In that sense, physics and data science are very similar to me, because you have a problem, a set of data, some tools, and a limited time to solve the problem, and at the end of the day all you want is to add value.
Asigmo: How did you learn about our program?
Diana: Before joining the Asigmo program, I had already worked for a year as a data scientist, so I had previous experience with real data in real problems. I got to learn about Asigmo through a platform called ‘Women in Data Science’ and after reading about it and checking its curriculum, I decided to apply and luckily passed both interviews and was admitted into the program.
Asigmo: What were your expectations from this program and could you share with us your experience?
Diana: Since I had already work experience in data science, I was in particular interested in the deployment week and wanted to dive deeper into machine learning and also in AI ethics lectures. The online modality was new to me though as I had never participated in a course that isn't face-to-face for 8 weeks! So it definitely took some getting used to, but once I got it, it was nice to work within a remote team and in the end, we built good friendships with other fellows! The different points of view raised in a diverse team is an important aspect to be highlighted, and this goal was very successfully achieved in this on-line version of the program. In fact, this is reflected by the special care the organizers demonstrated to bring together people from different time zones, backgrounds, and nationalities into one place.
Maybe, the most challenging weeks for me were Deep Learning and NLP weeks: the way these topics were explained was different than I was used to, even the terms that trainers used were distinct... and I totally liked it! because their explanations follow such an easy and understandable way. These two weeks were very special for me! In the AI ethics course, everything was new to me. To figure out how to put things in a different perspective and be in the position of the minority and underrepresented group are the main learnings here. Another equally important aspect learned in this course was how to design a model in order to be inclusive and unbiased which is one practice that I will definitely incorporate on my daily basis as a data scientist. Finally, the week of Cloud Solution and Deployment was very intriguing: you need to understand the general idea and adapt your solutions to the architecture to actually add value and contribute to your team.
Asigmo: What are your post-program plans?
Diana: For now, I am looking for a challenging data scientist position where I can practice all my skills and specialize in time series which is my favorite topic. I especially would like to work in an industry that brings value to society as a whole and works ethically and sustainably. I also have a passion for teaching and female empowerment, so I would like to do that parallel to my data science career!
2020 was a challenging year for us all and joining an intensive program like Asigmo was also a challenge. But to have a routine and a goal for my future helped me a lot to get through and to finish the program successfully! Now that the program is finished, I want to reflect on why I did this and how proud I am of myself to have successfully finished it, and now it’s time for me to focus on my career.
Asigmo: What is your advice to those who want to become a data scientist?
Diana: If you are out there thinking that you are really at the beginning of the way and want to become a data scientist in the future, start coding today. Just don’t be afraid of the screens! Learn Python, or your preferred language, and start reading simple things about data science and join the data science community. Read about algorithms, learn how to solve an interesting case of use, and code and code! I can't stress enough how important it is that you start coding today! Schedule one hour or 30 minutes per day to just focus on it, have a routine, and stick to it! also, practice the "think twice and code once" because this will save you an enormous amount of time.