How to find a data science mentor

And why it’s a good idea.

Russell Pollari
Towards Data Science
4 min readJun 18, 2021

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Photo by NeONBRAND on Unsplash

The world of data science, analytics, and engineering can be intimidating for newcomers. It’s a constantly evolving and fragmenting field.

As the industry evolves, new roles, niches, and tools are being created at a rapid rate. It was only recently that I learned about a growing need for Analytics Engineers — folks who can act as a bridge between Data Engineers and Data Analysts. Cookie-cutter curricula from MOOCs and boot camps can only get you so far. Curricula is inherently brittle in a world where in-demand skills change this fast.

Having a good mentor can be a major catalyst. A mentor can help you sort the signal from the noise — the hype from reality. They can reduce the information asymmetry inherent in the job market, guide you towards the best resources and tools, and help you sell yourself to hiring managers. Whereas a data science course meant for mass consumption must have broad appeal, a mentor can give you advice specific to the role and domain you are aiming for.

But without an existing professional network — and even with one — it can be difficult and awkward to actually find a mentor.

Every now and then, I’ll get a message that looks like this:

Hello, I want to become a data scientist, but I don’t know how to go about it. Please help.

I usually respond to these queries. But I’m an exception. I’m building and mentoring at SharpestMinds — a platform for mentorships in data science, analytics, and machine learning — which makes me a natural target for mentorship requests. Plus, I have a vested interest in understanding the problems of the folks who are looking for a mentor.

But this is not the right approach. The request is too vague. I can’t offer any practical advice without asking more questions. When you reach out to potential mentors with vague, open-ended requests — like “Please help”, or “Can you mentor me?” — you are creating more work for them.

It’s also not personalized. It reads like it was copied and pasted to dozens of others. If it seems like they put in little effort on their end, I’m less inclined to put in effort on my end.

Before you reach to anyone for mentorship, try and figure out what is exactly that you need help with. And, just as important, why you need this particular person’s help.

The best mentors are the people who have gone through the same thing you are and emerged successfully on the other side — working in a similar position that you are aiming for. But these people are busy now. They are working full-time as Data Scientists, Data Analysts, and Data Engineers. Many of them would love to help, however. You just have to make it easy for them.

Before you seek guidance, try to answer these questions on your own:

  • What kind of role are you looking for (e.g. Data Scientist, Data Analyst, Data Engineer, Machine Learning Engineer, etc.)?
  • What is the biggest hurdle between you and that role?
  • What relevant skills and experience do you already have? Have you done any MOOCs? Built any projects?
  • What tools, skills, or information are you lacking?
  • Is there a specific industry you’d like to work in (e.g. healthcare, finance, etc.)?
  • What kind of guidance would you want from a mentor?

Knowing the answers to these questions (and being transparent about them) will make it much easier for potential mentors to understand your needs and offer guidance.

Not having a definite answer to all of these is okay — it’s good to know where your ignorance is. And a mentor may be able to help you answer them. Many of the mentors I’ve interviewed for SharpestMinds, for example, mention that they enjoy helping folks understand and prioritize all the various data-related job titles. Others, however, would rather you have a well-defined career goal already. This is why it’s important to be upfront about what you know, and what you don’t.

On SharpestMinds, it’s acceptable to reach out to strangers for mentorship. But, in the real world, you’re better off building relationships first. You don’t want to appear out of the blue with a request for mentorship.

Start following people in the field that are active online (on LinkedIn, Twitter, Medium, etc.). Interact with their content — leave some comments, ask follow-up questions. If you got value from something they wrote, let them know! Flattery can go a long way.

While you do this, start learning or building in public (on LinkedIn, Twitter, Medium, etc.) where the same people might see it. You want to show potential mentors that you are self-motivated and driven. A mentor is not a teacher. They don’t want to spoon-feed you — they don’t have the time. Bonus points if you can show that you’re coachable. The best way to get a mentor’s attention is to show that you’ve already learned something from them.

Here is an example of a great intro message:

“Hi <name>, I read your Flask tutorial on Medium and got a lot of value from it. Thanks for sharing! I took some of your advice and made a simple front-end for my project here: <link-to-your-repo>. I was wondering, <specific follow up question>?

With a message like that, you’ve shown that you have a reason to reach out to them specifically and that you are self-driven and coachable. You’ve also prompted them with a specific question. Something easier to answer than, “I want to be a Data scientist, please help.”

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Towards Data Science
Towards Data Science

Published in Towards Data Science

Your home for data science and AI. The world’s leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.

Russell Pollari
Russell Pollari

Written by Russell Pollari

Machine learning and prog metal enthusiast. CEO at SharpestMinds.com—mentorships for data scientists.

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