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:
Content collaboration, even if it’s paid. If I’m made to write about something that I’m not naturally interested in, it’ll probably suck. >50% of calls with startups involve this: The answer is always “no”.
How to get your first job in data/machine learning or 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 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:
Advising your startup/team on data and machine learning topics, especially in the context of industry. This is my wheelhouse and I’m happy to help.
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.
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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