I enjoy helping, especially on the topics of data science, machine learning, and career. For a while, I responded to every email, and had an open calendar that anyone could schedule time on. However, that became unscalable. Thus, here are some guidelines on what I cannot, and can, help on. If you’re still unsure, shoot me a DM or email anyway.
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First, I think it’s good to explicitly state what I’m not much help on:
How to get your first job in data science / machine learning. My own journey is idiosyncratic, starting with a Psych Degree, then some lucky breaks and people who took a chance on me. I’m not sure how to help others replicate it. Nonetheless, I hope it provides inspiration that it can be done. Also see how others did it.
How to get into big tech. There’s plenty of people sharing their experience online, which includes how they applied, prepared, interviewed, negotiated, etc.
How to start learning data science / machine learning. I answered this question a while back; there are probably more recent resources now.
How to get into and do well in OMSCS. I’ve written an FAQ about it here.
Referrals if I don’t know you personally. This approach will most likely not work and I rather not get your hopes up.
Bugs, general DS/ML questions. Google and Stack Overflow will answer this faster.
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Here’s what I think I can contribute meaningfully on:
Answer concise questions via email on topics I’m familiar with (e.g., what I’ve written or spoken about). That said, if the question requires significant research, I’ll likely give answers off the top of my head and/or point you to other resources.
How to structure a data team, frame a data science problem, design a machine learning system, etc. I think about such topics a lot, both at work and in my personal time. Past consultations have been productive.
Resume/LinkedIn feedback for people with 3+ year experience. For more junior roles (i.e., <3 years), I don’t have much to offer beyond what’s on Google.
Introductions. Happy to provide intros to people I know, after checking with them that it’s okay. Do include a paragraph about yourself that I can send to them.
Speaking at conferences or podcasts. Grateful for opportunities to share about data science & machine learning in production, building & leading data teams, etc.
If it falls into any of these buckets, send me an emailI read everything but receive too much to respond to all of it. or schedule some time.
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