thomzi12

Yeah that's fair -- maybe just focusing on becoming an expert in data and ML engineering in the long-run is a more prudent career choice than totally dropping those for another corner of engineering. There's some wisdom here.

Taking that much time off of any job is pretty hard to do!

The real goal of a bootcamp though (besides networking) is adding a project to your portfolio. You can then show off this project to hiring managers to demonstrate your competence.

You don't need to do a full-time bootcamp to make this happen! I just checked and Flatiron school and Hack Reactor both have online part-time full-stack bootcamps. Also, while not as big of an investment, online platforms like Codecademy have career paths with a capstone project you can complete and add to your portfolio.

So, overall there are a variety of pathways to do this. Totally fair to point out though a bootcamp of some kind is a nice option in the off-chance it's a possibility.

You're right, Google has been very supportive -- very thankful for that! That said, if you work at a technology company, you CAN build a portfolio and self-advocate for projects with engineering teams your data science team already works with.

I think it's worth seeing how far you can get with this approach before interviewing for engineering roles at other companies.

One notable caveat with my approach: pursuing a portfolio approach took me a whole year to switch from DS to engineering. As you point out, grinding leetcode may only require half that time.

Yep. In any case, building a model is a just part of the puzzle -- serving it in production is a whole other skillset that is very valuable. imho

Yes -- one thing I struggle with is choosing whether to work on data engineering projects (which I know I'm good at and can provide immediate value) or challenging myself with more "traditional" full-stack engineering work where I can learn a lot.

Maybe a 60/40 mix is optimal

Hey everyone, OP here -- thanks for reading or discussing.

Curious if anyone else has switched from data science to software engineering, or has thoughts on comparing the two as a career choice. I'm all ears!

Sure! My company calls the role "software engineer" so that's how I describe the role but I think developer is also a good word for it