Data Science Overview: Maarten de Vries

Introduction

Hello, I’m Maarten de Vries! Originally from the Netherlands, I went to Harvard for undergrad. I started out interested in math, computer science and biology and took many disparate classes in those departments. Some students knew from day one that they wanted to be a doctor, or lawyer, or scientist, but I was not one of them. For most of my time in college, I felt like I was “keeping all options open”, taking classes I was interested in but without a clear plan for after graduation. Only halfway during my junior year, I switched my major to statistics because it offered a new computational biology track. It ended up being the best decision I could have made. To this day, the CompBio field is very exciting to me because the amount of omics data is ever-increasing, and we can use a wide toolkit of computational methods to demystify the secrets hidden within all this data.

Currently, I work as a computational scientist at Cellarity, where my daily tasks include managing large omics datasets to accelerate drug discovery, writing Python code, reviewing scientific papers, and building models for specific projects.

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career options

The field of computational biology offers a variety of career paths for those interested in merging biology with technology. These roles range from handling genetic data to developing models for medical research. Each position requires a specific set of skills and serves a unique purpose in the broader context of biological sciences and technology.

Depending on your academic background, there are different paths to computational biology. If you are a CS major who wants to work in computational biology, I’d recommend you at least take one or two biology courses. You don’t need to be an expert, but you need to know the basics. Conversely, if you’re a biology major, take an intro computer science class. It will make the jump to writing code to analyze your biological data a lot less scary. Regardless of your background, joining a lab and getting involved in research as early as possible will really help you think like a scientist.

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skills

What are the main hard skills you use on a daily basis in your current job?

Python Programming

Essential for developing and maintaining software, managing Git, and reviewing code within team projects. I learned some of the principles in my computer science classes, but most of software engineering details I learned on the job.

Statistics and Machine Learning

Applying statistical and machine learning techniques in biology requires a solid foundation in these areas. Here, I took classes in statistics and CS that gave me a good grasp of the basics.

Biology Basics

Understanding detailed biological data and disease-related information is crucial. I took several biology classes, though I did not work in the wet lab (in retrospect, I think it would have been useful to get some hands-on experience in the wet lab, at least for a semester or two).

What are the main soft skills you use on a daily basis in your current job?

Presentations

Regularly presenting complex technical details to diverse teams is a key part of the job. I typically present to my direct team every week and to the larger organization twice a year.

Team Collaboration

Effective teamwork is crucial for completing projects successfully. This is something you will learn on the job, though experience from student projects is certainly helpful.

Adaptability

Quickly adapting to new challenges and changes in project scope is important. Whereas the scope of homework and projects is usually well-defined in university, it is usually more fluid in industry. Priorities change, and you have to learn to plan for this.

Maarten

’s personal path

Tell us about your personal journey in

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:

Most people in computational biology have a PhD, which is valuable given the field’s complexity and the need for specialized knowledge. However, especially on the data science and engineering side, it’s certainly possible to break in before going to graduate school.

My own path involved undergraduate research and teaching experience in computational biology, and a willingness to learn. In terms of how I concretely found my first job, I ended up befriending a school alum who I met through a university career portal. When he was building his team, he offered me a chance to interview, where I presented on my research in undergrad. In short, university provides the opportunity to build the hard skills that qualify you for your first job, but do not underestimate the importance of networking.

What would you tell your younger you regarding building your current career?

Besides mastering the basics through coursework, I would stress the importance of engaging in scientific research as early as possible. In retrospect, I would have started earlier to build a portfolio of industry-relevant projects.

Final thoughts & tips

No one starts out knowing everything, especially in computational biology, where you need to know enough about many disparate fields. It can feel overwhelming to master computer science, statistics and biology. Fortunately, people in industry understand this well. You can almost see these skills as a set of sliders, and every computational biologist has these skills to a different degree.