How to Transition from Physics to Data Science: A Comprehensive Guide
Hi there!
I've often been asked about transitioning from physics to data science, data analysis, or machine learning, particularly by students and newcomers to the field. Considering that I get this question a lot, I thought it would be beneficial to share my experiences and insights on this topic. I hope you find this post helpful!
My name is Sara, and I have a Master's degree in Physics. Currently, I work as a Data Scientist at a global energy company.
In this post, I aim to share my personal journey into the data science career path with you, and offer some practical tips and advice for making a transition from physics to the field of data science.
Contents:
1- Why Physics?
2- Why the interest in Data Science/Machine Learning?
3- How Physics and Data Science are actually similar
4- Why Physicists Excel in Data Science
5- How to start the transition
- 5.1 Define your Goals
- 5.2 Define your Strategy
6- How can you start Learning?
7- How can you start Showcasing your Experience?
8- Finding a Job
- Make a Great CV and Cover Letter
- Internships
9- Other Tips and Observations
Hello there!
My name is Sara Nóbrega, and I am a Data Scientist specializing in AI Engineering. I hold a Master's degree in Physics and later transitioned into the exciting world of Data Science.
I write about data science, artificial intelligence, and Career Advice in these fields. If you want to read more, make sure you subscribe and follow me!
Why Physics?
Like many who study physics, I chose this field of study because of my deep desire to understand the world around me.
Driven by questions such as, "Where did we come from?", "How did the universe start?", "What is the nature of time and space?", and being a fan of Einstein's theories, I decided to study physics in university.
Maybe some of you can relate. Among my colleagues, motivations varied- some were drawn to astrophysics, others to particle physics, and so on. What drew you to your field of study? Was it curiosity about the universe, or something else entirely?
I had no idea what my physics journey would lead me into, and I sensed that many of my colleagues felt the same uncertainty.
Why the Interest in Data Science/Machine Learning?
After completing my bachelor's degree in 2019, I was introduced to Data Science, labeled as the "sexiest job in the world" at that time. Data Science was in high demand and was becoming increasingly popular, at least in Europe where I live.
I had to make a choice: either study astrophysics in my Master's or transition to data science. Surprisingly, I still chose astrophysics, since it was my childhood dream to study this field.
However, I also took advantage of an opportunity at my university that allowed students to take courses from other master's programs, so I was able to balance my studies between both fields.
So, that is what I did. Half of my courses covered topics such as the primitive universe, radio astronomy, and cosmology, while the other half focused on machine learning, statistics for data science, and learning programming in R. I was pleased to study all these fascinating topics, especially during the pandemic, as it helped distract me from the events happening in the world.
One of the reasons to transition was the realization that, while a physics degree is rigorous and versatile, it didn't fully equip me with ALL the necessary tools and skills for today's job market. Besides, most career paths for someone with a purely academic focus in physics didn't appeal to me, as I never saw myself in academia.
Also, a data science career was very appealing to me. It offered the opportunity to apply skills I had already acquired during my physics studies – such as Python, mathematics, and statistics – to a field that is both popular and suited for curious minds. Analyzing large datasets and extracting insights felt similar to detective or research work, roles that naturally attract many physicists.
So, another driving force for the transition was the desire to broaden my skill set and increase my versatility in the job market. And I won't deny it: data science also sounded cool and modern, which was certainly an attractive aspect.
