Finding a job as a computational scientist in industry -- version 1.0

Introduction

After going through a few job hunting cycles in industry, I went back and thought about what it was that I was doing when I was looking for a job and realized that I probably should have been far more considerate about the criterion that I was considering. I have been incredibly privileged and lucky at being able to find amazing places such as insitro and absci. However, I do wish I had thought about what I was looking for at each stage. This blog is an attempt to summarize my thoughts, experiences, and recommendations with job hunting as a computational scientist in the biotech space.

Criterion to consider

We spend a long time of our waking hours at work and I would argue we should be very thoughtful about our career moves. While I could go into detail about many different criterion that you should consider when hunting for a new job, I think Carta’s CTO Will Larson’s blog does the topic far more justice. Within the blog, he argues that at any given point in your career, you will always be balancing multiple personal criterion and you should think about how you want to allocate your rankings within them. The criterion to consider are:

- Personal criterion to consider 
  - Pace
  - Prestige
  - People
  - Learning
  - Profit

In my personal opinion, early on in your career you should prioritize learning, pace and people so that you can gain experience across disciplines and projects. However, as you age and take on increasing responsibilities profit and prestige will likely become an almost equal part of the equation. As you search through various job opportunities, you will often find yourself thinking about how to balance these criterion since its very unlikely you will find a job that checks everything for you to the fullest extent.

Finding interesting companies

Okay so now that you have thought about what you want in your next role, you can begin your search! It is entirely possibly that you already have several companies in mind that you think could be a strong fit. While there are many many ways to find companies, I think some sources end up being better than others. Things I have used in the past include:

1. Tapping into your network: In my opinion one of the best ways to find new companies is still to reach out to your network. This is easier said than done when you are just starting out so I would recommend cold emailing folks 3-5 years ahead of you in the same career and asking them about their careers and interesting companies.
2. Portfolio pages of biotech VC: Multiple VC companies (example 1) have portfolio company job boards that list 100s of open roles. Typically one of the nice aspects about this approach is that the VC team has already done (or should have done) a lot of due diligence on the company before investing so it increases your odds of finding a place with longer term stability.
3. Cold emails: I think cold emails to managers or execs within biotech rarely work. This is sometimes worth trying if you think you are a strong match to an open role and have personal interest in the company. Otherwise, often these emails are never answered. One interesting variation to this is to cold email university professors who spin out a lot of companies on if one of their startups might be a good fit for you potentially.
4. LinkedIn/Google/Social media: I usually find social media to be less than useful in finding companies but sometimes new company announcements etc are more easily discoverable here.
5. Recruiters: As you grow in your career, you will often get interesting recruiters coming your way with new opportunities. Sometimes these could be very interesting opportunities though often they will be offers from your direct rivals.
6. Journal & ML conference submissions: Recently, it has become rather vogue for biotech to submit their computational pipelines and models to ML conferences and scientific journals. Assuming you liked their paper and thought you might be a good fit, this might be a good option for cold emails.

Evaluating companies

Now lets assume that you have either gotten a bunch of offers already or you now have a very large list of companies that you need to pare down to a prioritized list. Here again, ranking each company along several axis might be helpful. Things you might want to consider are:

- Company criterion to consider  
  - Runway 
  - Location 
  - Stage
  - Public vs private 
  - Lab facility 
  - Compute facility 
  - Lab team size/quality  
  - Executive team quality 
  - Growth potential 

1. Runway: There is a huge risk involved in joining a place with less than a year’s worth of runway. However, it is unlikely that you will find a location that has more than 3 years of runway (unless its a large public biotech/pharma).
2. Location: Unless your job is fully remote, you should consider the physical location. In particular, are you okay with moving for the job or are you comfortable with the commute? We live in a time where hybrid work schedules are becoming more and more common. So a longer commute might not be entirely unreasonable though you should probe your hiring manager to see if they forsee this situation changing in the near future.
3. Stage: Without infinite funding, pre-clinical vs clinical stage companies have a very different set of folks that call the “shots”. This leads to different set of projects getting funded. This is more common in smaller biotech compared to big biotech/large pharma but can become an issue if you are potentially being hired for a risky capital intensive project and the biotech company is also running several clinical trials in parallel.
4. Public vs private: There are many advantages and disadvantages to joining a privately held biotech vs a larger publicly traded biotech/pharma company. This likely requires a full on follow up blog post but you should be thinking about the value of your equity, potential exit opportunities, and company stability for a samller private biotech. For a publicly traded company, you often have far more stability but a lot of times your equity upside will be limited (unless you are lucky enough to catch a wave like the GLP-1 agonists at Lily or Keytruda at Merck) and many times these companies will have restructurings and layoffs to appease the capital markets.
5. Lab facility: Given that you are a computational scientist, having the ability to validate your predictive models should be high on your list of requirements from a place. If they are planning on building out a lab facility, be prepared for months, if not years, of waiting for validation. Lab facilities are incredibly difficult to build and staff properly in my experience.
6. Compute facilities: Given that you are a computational scientist, having the ability to train your models predictive models should be high on your list of requirements from a place. Do they have adequate access to CPUs/GPUs? Can you access them easily? How stable is the LIMS system? Does data still mostly flow via unstructured CSVs and slack messages or do they have enough infrastructure in place? Depending on what stage of the company you join (or how much they care about modeling), the answer here will vary.
7. Lab team size/quality: Does the biotech have the right set of folks already employed or planning on getting them? Do the lab folks seem excited to collaborate with you or others in the compute team? Do they consider you as an equal on the experimental design side or do they seem skeptical of computational tooling. Ask to have at least one potential experimental collaborator on your interview panel and ask open ended questions to probe these things.
8. Executive team quality: Are there drug hunters on the executive team? Or have they built out other platforms before? Generally, you do want to know if the executive running your organization can articulate what success looks like, possess humility, is open to suggestions, and would be willing to put themselves out there for their team. I think evaluating executives on the 5 levels of leadership is often helpful. This is often harder than it looks but again asking open ended questions about growth opportunities, turnover rates, management philosophy etc can help you gauge some of this.
9. Growth potential: In my opinion, this is often incredibly hard to judge and you should probably not evaluate a location on “potential”. It is far safer to assume that what you see is what you will get. Are you still able to grow along the criterion listed/ranked above in the length of the company’s runway?

Final thoughts

In Islam, there is a hadith from our Prophet Muhammad (PBUH) that I like that says: “Tie your camel first, and then put your trust in Allah.” Ultimately, you will never really “know” if your job choice was the optimal one. You will have FOMO about jobs not taken and uncertainty and doubt about the ones that you did take. The best you can do is do as much due diligence as possible and then take a leap of faith. In the end, you will be okay.

Sources

https://lethain.com/forty-year-career/