I'm a web and data generalist, in my 4th year of an undergrad in CS. I started speaking with Yonatan ~3 months ago while starting to apply for my first full-time job.

Some ways he's helped:

• Convinced me to apply to positions I hadn't expected to receive interviews, let alone offers for. Positions I'd been eyeballing for YEARS.
• Got me to defer accepting offers I felt lukewarm about, and complete multiple interview cycles in the meantime.
• Provided Social Accountability as a Service to get off my ass on personal projects.
• Helped me to clarify my next goals + todos by speaking actionably about them with someone else.

I wish we started speaking years ago. I think I'd be in a very different place now. I've had technical mentors in the past-- professors and senior work colleagues. None have been as helpful as Yonatan. 

• He's the first to genuinely care about my personal long-term growth, and share my core (EA) values.
• He cares deeply and thinks regularly about decision-making and professional advice-giving on a meta-level, and it shows. I've had mentors who on paper should have been a great fit, but weren't great at giving advice to someone much younger, outside the specific thing we were working on. These are all things Yonatan is great at. He always comes through with great advice, from a perspective I hadn't considered.

If you are in a similar place in your career, or anxious/uncertain whether this would be helpful for you: I'd highly recommend reaching out to him!

• He's easy-going, pragmatic, and takes a mentee-first approach.
• Also, he's a pleasure to speak with.

Thoughts on data science questions from myself (worked 2 junior data science positions after ~1 year of self-study) and my circles (mostly DS/ML at tech orgs):

How to decide whether data science or software engineering would be a better fit for someone?

• Data science work involves more uncertainty and longer iteration times (i.e. debugging workflow is more of an art and takes half a day as opposed to a minute). Does this sound like a pro or con?
• DS/ML hiring managers care more about pedigree. Your resume may be auto-filtered by HR/scanning software if you don't have a graduate degree in ML/math/stats/computational science. Do you have one/would this be of interest to you? 
• What areas of DS/ML are you most interested in? Depending on what that is, SWE and DS work may not be mutually exclusive: Look into positions in analytics engineering, ML engineering, data engineering, software engineering for telemetry/observability (common in organizations with more mature analytics departments). 

How can someone study at home and find their first job in data science?

• Potentially useful blog post from a friend of mine, that mirrors the path I took: https://nicholasvadivelu.com/2020/08/30/learn-data-sci/

Would you like to mentor data scientists sometimes? I’d be very open to special requests, like “only people in stage X of their career”, and you can also decide to stop any time.

• I'd be willing to mentor data scientists, though would probably only be useful to people more junior (i.e. finding their first job in data science).