(Note: This is my happy success story about finding a new job - I want to acknowledge that it’s ill-timed with the tech layoffs that are happening now. Finding a job when you didn’t choose to leave yours kinda sucks, even if it goes well. If you were affected, I wish you a quick search and a better job than the one that’s behind you.)

When I was looking for my first job outside academia, I heard over and over again that the second job after a career switch is easier to get. It was an important thing to keep in mind while searching, because that first job search was pretty difficult. Knowing that it was unlikely to be this bad again helped me get through it and make peace with finding a first job that wasn’t perfect - since it wouldn’t be as hard to find the second one.

Recognizing a poor fit

My first post-academic job, at everphone, was very good in a lot of ways. I worked well with my manager and the rest of the Business Intelligence (BI) team. The company supported me financially and logistically in German lessons and paperwork to pass my B1 german test and get my permanent residency. I learned a ton about the coding side of data science and data engineering (ETL pipelines, clean code, unit tests, etc.) and typical workflows (sprints, tickets, etc.)1.

Around a year into the job, though, some of the small irritations were growing into larger dissatisfaction. BI was working a lot with finance. It took months to get feedback from them on anything they requested, which led to long, frustrating development cycles. They also insisted that results should paint a rosy picture of reality instead of providing useful information on how to improve. My values were at odds with the company; they were quite sales and marketing focused. And on top of that, I wasn’t pleased with the way raise negotiations went.

So I started job searching, though slowly. I turned my LinkedIn to “open to new opportunities” stealth mode and would search new jobs anytime I felt bleh about work (on reflection, this was anytime I met with folks outside BI and engineering). Despite my complaints above, my day-to-day at the job was still good, so I was pretty sure I could make it to a full three years there if nothing better came along. Searching from a position of strength is one of the things that made the job search far easier.

When I was looking for my first post-academic job, I knew I wanted to void marketing, military, and finance industries, but other than that my wishes were somewhat generic - things like “getting along with my manager” and “opportunities for growth”. On this second job search, I had much stronger and better-infoled criteria for what would constitute a better job for me:

  • Data from the physical world. There were still interesting problems I wanted to solve with phone pricing - I wasn’t bored with my dataset. But I missed getting to apply my scientific intuition to problems. I also realized that working with non-money data would likely separate me from the finance department of a company.

  • At least one other data scientist. At everphone, my manager and I were the only ones writing analysis code and data science pipelines - and he was only doing it with <10% of his time. I wanted either a more direct collaborator, or just someone working on similar enough stuff to bounce ideas off of.

  • No reduction in compensation. It’s a recession, and my rent is going up. More money would be nice, but given Berlin salaries and my refusal to work with marketing or money, this was the line I could draw.

  • A hybrid office situation. I worked nearly 100% remote at everphone. It was still the height of COVID, and my option for in-office was a 20-person room with no policies around vaccination and testing. Huge no from me. I don’t want to be in an office every day, but was missing the social interaction and ties with my colleagues that are (for me) easier and more natural in person.

An order of magnitude more chill

My first job search (discussed here) included 100 applications to get a position. My second job search included 7 applications and 3 conversations with recruiters. I interviewed with two different companies, and got offered one job. I didn’t do a focused search but just threw in a couple applications a month.

I also answered recruiters. I am not (yet?) so desirable on LinkedIn that I get constant recruiter spam, but after about a year of data science experience and a profile set to “looking” I started getting messages at about once a month. These were a bit of a mixed bag, some clearly not well-suited to me, and others that I saw the point in learning more about. I talked to two that had some non-specific opportunities that didn’t quite fit my profile.

And then a recruiter messaged me the day after I had an absurdly bad meeting at everphone2 about a Data Scientist/Physicist position - which even from the title looks like a promising fit.

A great fit

That job - the one I’m currently at - is at GrandPerspective, a company that uses spectroscopy to detect hazardous gasses in the air at chemical plants. I did not expect my years of experience with spectroscopy to be useful outside of astronomy, and was so excited to find that they could be. My technical interview involved reading a paper with some radiative transfer3 equations; seeing those equations again warmed my little nerd heart. My data science experience was also surprisingly well-tuned to their needs (ETL pipelines rather than heavy machine learning).

After the technical interview I asked if I could visit the office, and that turned into an informal group interview. That could have been unsettling, but it felt easy and chill. At the end of it, the project manager asked me “so, have you made up your mind?” which I didn’t know how to respond to, given that I didn’t have an offer (yet). I got the impression - which has been since confirmed - that they were as excited to find me as I was to find them.

The offer came (a week after that in-person meeting, and about a month after the first recruiter contact), then some negotiations4, and then I accepted. I started the new job in November of 2022, so now I’m about three months in.

And this job is an amazing fit for me. I’ve learned a lot about interferometry and the instrument they use and the analysis already happening. I’m feeling well-integrated and valued within the data science team and the company. It’s not perfect, and I’m adapting to some new things, but I feel more grounded than I have in a long time, because my work is again something I identify with.

Not just good luck

I feel quite lucky to have found this job - especially so soon! I think that even without the luck, I still would have had a relatively chill job search and found something that fit slightly better than my first job. I had a better idea of what I wanted at work, and companies were more willing to trust that I could adapt to non-academic work with a year of experience. So it’s easier the second time around.

  1. If you’re interested in a post where I define data science + business things that were new to me, please send me a note! 

  2. I did mention to my manager before I left that that is indeed how bad the meeting was. He was on vacation at that time. 

  3. Radiative transfer describes what happens to bits of light between where they are generated and where they are are observed. 

  4. I’m tempted to write about this offer negotiation as well, since it was more difficult than I thought it would be! I was well-supported by my partners here.