Graydon Snider –Part 2 – Building Your Path Towards Data Science

In part 2 of my conversation with Graydon Snider, we dug a little deeper into his rationale for exploring career avenues during his postdoc. The strategies and resources he used, the people he met, the notes he took. I also took the opportunity to ask Graydon what the day-to-day of a data scientist looks like today and how to prepare if you want to access this flourishing domain.

Graydon Snyder

Graydon grew up in Ottawa, then moved to Montreal for graduate school for a PhD in chemistry at McGill University, moving to Halifax for work as post doc at Dalhousie University, and finally came back to Montreal where he currently works at SSENSE as a Data Scientist. Formerly a student of atmospheric chemistry, Graydon carried an interest in numbers between various pursuits. His hobbies include running and juggling, occasionally at the same time.

What you’ll learn about in this episode:

  • How having informational interviews and collecting narratives of people from your domain who have transitioned out of academia can help you find your path
  • What you need to unlearn when preparing to interview for a position in industry
  • The importance of networking and of showing up for events where you might meet people with whom to discuss your professional future
  • Taking advantage of online training platforms to get your programming skills up to speed
  • Why you should look for career-related training and seminars in your university
  • A good starting point for data analysis and programming: R

This episode’s pearls of wisdom:

“The three things that you would want to emphasize in an interview that academic institutions don’t teach you by default are: #1 is most interviews end up being “do I want to work with this person”; right under #1 is #2, which is “do they have the specific skills” but that’s something you’ve lost control of. You do have more control over showing how you can network.”

“Learn how to apply to places that you didn’t think about, necessarily, initially. What I mean is don’t go with the most obvious choice. I fell into this trap myself. Even with all these skills and everything, I was still thinking about chemistry. Why not just apply to all kind of institutions? Big companies have all kinds of special positions like data science.”

Graydon’s links: LinkedIn –;

You might also like the following episodes:

Jonathan Weitzman – Academic Mentoring:;

Maryse Thomas – Science Communication:;

Nathalie Ross – Medical Writing:;

Zoë Ayres – Water Industry:;

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