How to Get a Job as a Data Scientist at Hulu
By Sarah Grant | October 2, 2015

Cheat Sheet, a regular series, offers an inside look at the hiring process at some of the best places to work. This week: Streaming video service Hulu is expanding its staff of data scientists—a growing team that can turn a whiteboard equation into the next binge-watching rabbit hole.
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Interview Cheat Sheet #12
The Job
  • Hulu
  • Position:
  • Data scientist
  • Hiring Manager
  • Aysegul Cansizoglu
  • Principal software development lead, data science
  • Salary:
  • $120,000 – $200,000
  • Description:
  • Analyze what people are watching on Hulu (or what they would like to watch) to build more personalized show recommendations.
  • Qualifications:
  • Master’s degree in statistics, math, or operations research; experience with scripting languages (Python, Ruby); a love of deep data analysis.

The Method

First Round:

A 30-minute phone screening with a recruiter who assesses the candidate’s background. “Experience will help, but it’s not everything. We expect candidates will learn a lot once they are here.”

Second Round:

Phone interview with the hiring manager, during which the applicant is asked to solve a case study relevant to the streaming industry; light coding questions that can be answered on a coding pad.

Third Round:

All-day interview with the hiring manager, data science lead, business partners, and CEO. Candidates mimic a real work experience by solving a complex, open-ended problem on a whiteboard with the data science. “We want to see the steps of your thought process and communication skills.”

The Score:

The hiring decision is made by a jury of members involved in the interview process. If one person has a strong opinion, it’s her job to convince the group that the candidate has skills the current data science team lacks.


How to Ace It

Do stay aware of tech trends in your field. “This is a changing industry. Knowing the current literature on streaming is a plus.”

Do share good business practices from other jobs. “We had someone with a retail background come up with interesting and unique sales solutions that no one else would have thought of.”

Do be persistent and accurate. “What we evaluate is impact, and getting it right. Our work isn’t necessarily deadline-driven.”

Don’t hold back if you think Hulu is doing it wrong. “I gave an offer to a candidate who took my problem guideline and said we should change the whole structure of the operation.”

Don’t fret if you aren’t the complete package—yet. “No one has the same work experience here. Someone may not be much of a coder but is great with business modeling. We are looking for potential.”