Career Advice for Firefox Contributor
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I worked at Mozilla for three years, and loved it, despite the lack of leadership at the company at the time. I still am zealous for open source due to my Mozilla experience. I could have stayed there forever and been happy, but Google made me an offer I could not refuse.
Yeah, their mentored bugs program for contributors is great, and if I wasn't concerned with my career trajectory at the moment I would probably just continue out of pure interest & for the learning opportunities.
Do you think career advancement from continued contributions is likely in my case though? Or should I invest my time elsewhere?
Do you think career advancement from continued contributions is likely in my case though? Or should I invest my time elsewhere?
Understanding the process and workflows to being a productive open source contributor is useful. But perhaps find an open source project where the stewards are actively hiring and pay well.
Nearly finished my CS postbacc degree with a perfect GPA while working. All hell broke loose as soon as I started studying, with never ending family issues throughout, which really stressed me out.
I made a couple of contributions to the Firefox browser in C++. The 2nd one quickly had me delving into C++ template metaprogramming with meta functions to complete it. The mentor at Mozilla gave me some great tips as well. This was very rewarding personally and a great learning experience, but so far has not resulted in any increased attention from job applications (have sent out many recently with the contributions listed on my resume) – zero interviews, all rejections so far. I’m all over the place, can’t seem to pick a direction & it seems I am crap at planning out my career. Picking a direction and focusing on it seems necessary in this competitive environment.
which option should I choose to increase earnings in the future (in Canada, can’t move to USA)?
1) continue contributing to Firefox and focus on SWE applications
2) refresh ML/stats knowledge and contribute to numpy or other data related OSS and apply for data scientist/ML positions
3) try to pivot into the data engineering team in my area and go all in on DE
4) focus on leetcode interview prep
5) OSS contributions in languages such as Java/C# (I thought of trying to contribute to Apache Cassandra)
6) focus on business ideas instead of employment, given high taxes & low Canadian salaries: learn webdev and start a SaaS
7) learn gamedev and develop an indie game (probably ridiculous for me to pursue, web/mobile dev seems more practical..though I don’t have experience in either)
8) other?
I’m thinking the most pragmatic choice would be to focus on ML (option 2), maybe go for a masters at some point, create a LLP/corp for ML consulting when I’m confident and invest in S&P 500. This is a long road though, and I feel like I’m just wasting my time whenever I crack open an ML textbook to start studying. In fact, I get this uncomfortable feeling with any other direction I consider at the moment.. since the only work exp. I have is in analytics & resume screeners/recruiters don’t seem to care about anything other than work experience. ———-
Background:
I work in IT in the public sector (pension, decent benefits etc), but the role is focused on supporting data analysts/scientists in the business area. I also have a bachelors in Econ, and prior to this job, I was a data analyst for years (and got the attention of a manager in IT, which is how I secured this job). The pay is decent (but not enough for buying property), but everything moves slowly and I’m not learning much. Too much paperwork, and hardly any software dev. I’d like to experience another environment, for a year at least, and I’d be happy with either a SWE or data scientist/ML eng position. I should note that I’m not willing to take a salary cut… part of my motivation is feeling pressured to increase my income as life in Canada is becoming less affordable every day (housing crisis etc.). I’m over 30 and still renting.
Should I just refresh ML/stats/math knowledge (which is very rusty after years in a slow moving environment) and contribute to data related OSS like numpy or PyTorch, read textbooks like “mathematics for machine learning”, and focus on getting a data scientist/ML eng position? I question the ROI for this though since I don’t have a MS/PhD. I am also not ready for a leetcode style interview, so maybe another option is to just focus on interview prep. I’m trying to do 1 leetcode per day while taking a CS course, working, contributing to OSS, and reading textbooks… I’m very possibly spread too thin, and it feels like I’m just spinning my wheels. Any suggestions are appreciated!