Networking like a pro in data science
By: Jeremie Harris
Tags: Tds Conversations, Tds Podcast, Networking, Data Science, Towards Data Science

Networking like a pro in data science

Sanyam Bhutani on the TDS podcast

Editor’s note: The Towards Data Science podcast’s “Climbing the Data Science Ladder” series is hosted by Jeremie Harris. Apart from hosting the podcast, Jeremie helps run a data science mentorship startup called SharpestMinds. You can listen to the podcast below:

Networking is the most valuable career advancement skill in data science. And yet, almost paradoxically, most data scientists don’t spend any time on it at all. In some ways, that’s not terribly surprising: data science is a pretty technical field, and technical people often prefer not to go out of their way to seek social interactions. We tend to think of networking with other “primates who code” as a distraction at best, and an anxiety-inducing nightmare at worst.

So how can data scientists overcome that anxiety, and tap into the value of network-building, and develop a brand for themselves in the data science community? That’s the question that brings us to this episode of the podcast. To answer it, I spoke with repeat guest Sanyam Bhutani — a top Kaggler, host of the Chai Time Data Science Show, Machine Learning Engineer and AI Content Creator at H2O.ai, about the unorthodox networking strategies that he’s leveraged to become a fixture in the machine learning community, and to land his current role.

Here were some of my favourite take-homes from the episode:

There are many, many different ways to network in data science: Meetups, Slack and Discord communities, one-on-one calls, podcasts, written interviews and blog posts, etc. You don’t have to do them all — and you shouldn’t. Instead, start by picking the strategies that align with your personality. If you’re more introverted, stay away from Meetups (where more ice-breaking is required) and focus on one-on-one calls. If you’re more of an extrovert, seek opportunities to give presentations and exploit your comparative advantage by engaging with people at larger group events.

This might sound controversial, but podcasts are still under-valued as a way of networking. Don’t get me wrong: you should absolutely not start a podcast to become famous! But an interview-style podcast gives you a great excuse to get to know important members of the machine learning community, and even managers at companies you might someday want to work for. People are surprisingly open to being interviewed, and a one-on-one format means this strategy is especially well-suited for introverts.

Hosting a podcast is also great if you’re having trouble working up the courage to network, because it forces you to pre-commit to speaking to someone at a specific time and date. It’s relatively easy to work up the courage to send an invite by email, so it’s something shy introverts are more likely to actually do — and once you have, you’re forced to follow through with the conversation!

There are tons of great Discord and Slack communities as well as online forums where you can connect with other data scientists to get warmed up before doing any “face-to-face” (i.e. remote videochat) networking. This is probably a good first step if you’re looking to dip your toes in the water.

You can follow Sanyam on Twitter here, and you can follow me on Twitter here.

Also, check out the Chai Time Data Science Show on YouTube and on Anchor!