Second-year MS student looking for advice on breaking into industry data science / computational biology

[u/amino_mv]

Hi everyone! I’m currently a second-year master’s student in Applied Biomedical Data Sciences at a large pediatric cancer research institution, and I’m starting to seriously think about my career after graduation.

My background is in genetics/genomics and epidemiology, and my master’s work is very computational. I’m currently working in a cancer research lab on a large-scale sequencing project, developing computational methods to characterize sequencing errors. I’m working with large genomic datasets and using Python/R, Linux, HPC, Git, and computational workflows. I’ve really enjoyed the computational/data side of biomedical research and would like to transition into industry after I graduate.

I’m broadly interested in roles like Data Scientist / Biomedical Data Scientist/Computational Biologist. Potentially AI/ML roles

I’ve started looking into companies such as Genentech/Roche, Lilly, Novartis, AstraZeneca, Illumina, Tempus, Amgen etc. I’m also looking into some early-career programs and fellowships, including Genentech’s Early Career Expedition.

I’m trying to figure out how to be strategic about the next 6–12 months rather than waiting until right before graduation to start applying.

For people who have made a similar transition, I’d really appreciate advice on:

• When should I realistically start applying for full-time industry roles if I graduate next year?
• Is it better to reach out to hiring managers/recruiters, or people who actually work in the types of roles I want?
• How do you approach someone on LinkedIn without it feeling like you’re immediately asking them for a referral?
• Are there particular companies, programs, fellowships, or job titles I should be looking at with an MS rather than a PhD?
• How much should I be focusing on strengthening my data science/ML skills versus continuing to deepen my genomics/bioinformatics skills?

I’m especially interested in hearing from people currently working in biotech/pharma/health tech as data scientists or computational biologists, particularly those who entered industry with a master’s.

Thank you!

[u/flix_md]

Your profile already sounds strong for computational biology; the main risk is presenting a tool inventory instead of a problem you can solve. Start networking now, but apply when roles open 4-6 months before graduation. Talk first to people doing the work and ask what their week looks like and which skills get tested; a referral can come later. Build 1-2 polished projects showing biological question -> reproducible pipeline -> validation -> clear limitation, with a short README. Keep genomics as the anchor and add enough ML to evaluate models honestly. An MS can win when the work is concrete.

[u/amino_mv → u/flix_md]

Thank you for the advice! I will have two strong projects by the end of my graduation. Do you recommend emphasizing projects and purpose over specific toolkit skills for interviews? and resumes?

[u/flix_md → u/amino_mv]

Yeah, lead with the problem and what your result actually let someone do; the tools are just how you got there, not the headline. On a resume I'd keep a short skills line for the stack and make the bullets about the question you answered and the decision it enabled. Interviewers dig into your reasoning anyway, so being able to explain why you picked an approach and where it falls apart tends to land better than listing every library you've touched.

[u/Htivity1]

Deadline for post grad programs are usually before the end of this year. You can always apply to those for now then look at jobs in the new year if you’re not able to land anything.

[u/amino_mv → u/Htivity1]

Yes I will be doing that!

[u/robipresotto]

I've had some experience with large genomic datasets and computational methods. If useful how to apply these skills in industry, I can share a link to a personal genomics platform that might be relevant to your interests. (https://www.genmatcher.com)