Consider working on genomics

I had a job similar to that at a similar places (actually places), but I ended up leaving because I was a one man team and got burnt out. Writing software for scientific purposes and true R&D is very fun and interesting, and I think there is a lot of untapped potential for doing some interesting things there. But there is a balance between the wild west, then what your first described, and then what you later described. Keeping things organized enough to not be chaos but loose enough to not get siloed.

For me, working in the field is worth doing because I have come to a place in my life where I value doing something useful more than I value other things. You really can't put a value on being able to get up every single day and know that you are actually doing something good for the world that day. And getting paid, while less than your absolute highest potential, still a really good salary by comparison to most of society.

Plus you do get a lot of freedom and autonomy, and exposure to absolutely fascinating research and biology, and if you want to dabble in academia, it's surprisingly easy if you have a supportive group.

I’m in the “bunch of software people together” department so it’s not as insular or PI driven as working in a lab.

I still mostly like the role but it has become more generic over the years as the department acquiesced to the working ways & programming languages of outside private funders.

1. Compensation – In academia, you will likely take a big salary hit (much of this is discussed). There are a few exceptions like newer institutes like Chan Zuckerberg, Arc Institute, etc that are paying much more competitive salaries though. In well-backed startups and larger biotech/pharma, cash is likely equal (or often more) to software comps elsewhere – the bigger hit you take is usually in equity – no one has been able to match FAANG on total comp with RSUs in the mix. Startups can provide options, but it's not very fungible. For example, we benchmark salary on comparable A16Z pre-public non-bio companies use as well as stats from the broader SV SWE salary datasets. There are startups in bio that pay even higher to lure talent.

2. Research vs Product – Over the last decade, there are a bunch of highly profitable tech companies and large funded new startups (e.g., Calico, Altos, Deepmind, etc) trying to take on bio as the next frontier. These places (like those named in the blog post) pay very competitively. Thus far, these places often turn into a big mess because it becomes hard to deliver products (like drugs) in a mostly academic-y atmosphere. I don't think anyone has really cracked this nut yet (or if it's even possible).

2. Culture of SW importance – In a lot of startups these days, this has changed quite a bit over the last 5 years. Lots of software & data science first startups. I think in the larger pharma/biotech though, the centrality of drug discovery takes a lot more oxygen than software, which are often thought of as innovation bets and different places have different levels of long term commitment.

3. I think one important difference is the type of company. There are many software companies in healthcare/bio that are software products supporting R&D, healthcare, drug development etc. Many of them have done quite well (e.g., Benchling, Komodo Health etc in A16Z portfolio alone) and are basically just software companies that just happen to be in bio. There are many others like most drug discovery companies (like us) where software and data science is enabling, but the product is often ultimately drugs. For a lot of SWEs, this becomes problematic because people often want the satisfaction of having externally deployed software products to push into the world. The heroes and heroines of this world are often drug hunters over tool developers, and this has cultural consequences as well. Some people are really good with this (getting a lot of satisfaction out of enabling new drugs to treat serious disease), but a lot of folks aren't.

4. The current biotech crash has been bigger and more sustained than the tech crash thus far. High interest rates impact this industry much more than others, because revenue on new drugs, which drive a large part of the industry usually take a decade or more to develop before revenues are flowing. This is less of an issue in healthtech companies that can often deploy much more quickly (90% of healthcare costs are not drugs).

5. Finally, there are many happy SWEs and DS in bio at companies that value software and can build good careers in it building products that ultimately help human health in new ways. It's a pretty amazing time in biology, with a suite of new technologies to read, interpret, write, edit, deploy molecules/DNA/cells that are really unlocking many of the mysteries of human diseases. I feel lucky every day we get to continue building in this space.

At one point we wrote an internal tool (I think lots of organizations do this, since all the 100s of existing tools somehow don't fit, so you invent #101) and while it was tremendously satisfying getting batch jobs with 1000's of cpu's churning away, that kind of data infrastructure needs to be standardized. I think some companies are doing this, e.g. saw a presentation about Arvados/Curii that seemed interesting (but haven't used it so not sure). Maybe CWL will turn out to be the way forward here?