My Journey from Econ PhD to Tech — Part 1: Interview prep + Networking

Tell us about yourself

I’m a PhD in Economics at Stanford. In Jan 2021 I’ll be joining Google as a Data Scientist, working on bidding algorithms under Display Ads.

Why not academia? Why tech?

There has always been two things I wanted to do in my life: (1) understanding how the world works and (2) making positive changes in the world.

How did you tell your advisors about it?

I had a very easy time because all my advisors/committee were cool.

How did you get started collecting information?

Although econ grad school prepares us for a data scientist career in tech, to actually get a job, there’s still a lot one needs to learn — not just skills like python and SQL, but also understanding the tech world in general — how is a tech firm set up, what’s the universe of job (or job titles) a econ phd can reasonably apply for, what’s the differences between them. When breaking into a new field, the hardest part is that you don’t know what you don’t know.

  • If I seriously want to go into tech, seriously preparing for the interview is important, because tech interviews ask for things like python, ML, and SQL, which I know nothing about
  • Networking and referrals are important

How did you prep for the interviews?

I’m someone who prefers to learn things in a systematic way, i.e. through a course. But at that time, I clearly don’t have time to take academic courses from Stanford or Coursera to learn about Python, or different types of ML, or algorithm and data structures, or SQL. In addition, courses taught by universities tend to be too theoretical, not practical enough, and contains too much details. If you’re interested in learning something just to find a job, there are much more focused materials: Data Science bootcamps.

  • Algorithms and data structure: Laioffer class+using their internal tool ‘Laicode’ (very similar to Leetcode)
  • SQL: Laioffer class + Laicode + Leetcode + w3school
  • Python — Data manipulation and numerical computation: Laioffer + EDS + googling around + doing Quora’s data challenge in python instead of Stata
  • ML knowledge, and ML projects to put on CV: EDS class+googling around
  • Experimental design/causal inference/Stats: Laioffer class + googling around + reviewing Guido’s second year sequence notes (which turns out to be not super useful because it’s still too theoretical)
  • Behavioral questions: googling around + thinking hard about my past project experience
  • Open-ended case study: watching youtube videos of talks that the firm’s DS team gave in universities (the recruiter sent me links; and on youtube, once you start watching the first video, it gives you recs for similar videos); reading the firm’s data science blogs/papers; talking with Anthony for 1 hour about the firm’s business model/what questions they might be solving

How did you get referrals?

  • I pinged the Stanford econ (or GSB) phds who were just done with the market and went into tech (whom I either already knew or got to know through the department’s ‘job market candidate panel’).
  • I looked through Stanford econ department’s past placements*, identified everyone who went into tech, searched for their email online, or LinkedIn direct-messaged them. Some replied; most didn’t. (*note: placement = where an econ phd end up in her/his job search)
  • I contacted the panelists in RE’s event whom I thought were not too senior.* (*note: Now that I think about it, I really should have contacted all of them. In academia if you send a cold email to a professor at a good place asking for a 15 min chat to learn about ‘career in econ’ I highly doubt anyone would reply. In tech, in general, things are less hierarchical and people are more friendly/open minded.)
  • One of my advisors put me in touch with one of his former student who is now in tech.
  • During this period of time, I posted some questions on WeChat 朋友圈 (similart to twitter ‘tweets’) about job hunting (e.g. “what on earth is a ‘applied statistics case study question’ in a data science interview???”), and some of my friends, upon seeing them, private messaged me to offer help and/or ask if I’m interested in applying for their firms.
  • Anthony posted on his Twitter ‘My wife who is a econ phd at Stanford is looking for data science jobs in tech. Ping me if you have openings or know who’s hiring.’ and got ~10 replies.*

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Scarlet Chen

Scarlet Chen

CEO@robinland.io. Senior Data Scientist@Shopify. PhD in Economics@Stanford. Ex-google. scarletchen.com