Data Scientist, Pricing

Stripe (View all Jobs)

US-Chicago, US-NYC, US-Seattle, USA (Remote)

Please mention No Whiteboard if you apply!
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Interview Process

1. Programming/debugging phone screen 2. On-site with your own laptop/setup and full access to internet. Interviews include systems design, 45 min practical coding question, integrating an API exercise, debugging, and talking with hiring manager about team alignment.

Programming Languages Mentioned

SQL, R, Python

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

At Stripe, you’ll be part of a rich Data Science community for Analysts, Scientists and Engineers to learn and grow together. At the same time, our embedded org structure means that you’ll be working closely with our Product Pricing partner team.

What you’ll do

As our business increases in complexity, we are continually seeking to optimize the pricing of our growing suite of products. As a data scientist partnering with the Pricing team, you will have the opportunity to both directly (via experimentation) and indirectly (via causal inference) measure the effect of pricing decisions. We are looking for someone with a research-oriented mindset who can also propose new ideas for pricing directions. This work will be highly visible to senior leadership and has the potential for significant business impact. If this sounds exciting, we’d love to hear from you!


  • Act as an embedded partner to the Pricing team, bringing a data-driven perspective to achieving the team’s goals. As the partnership develops, suggest new projects and potential areas for collaboration.
  • Lead experiment design, analysis, and interpretation for new pricing initiatives
  • Apply causal inference methodologies to understand the effects of changes that can’t be measured directly
  • Partner with User Research to understand the user-facing impact of pricing changes
  • Drive the collection of new data and the refinement of existing data sources
  • Communicate results to senior leaders across Finance, Data Science, and Product teams

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

  • 5+ years experience working with and analyzing large data sets to solve problems
  • A PhD or MS in a quantitative field (e.g., Economics, Statistics, Sciences, Engineering, CS)
  • Expert knowledge of a scientific computing language (such as R or Python) and SQL
  • Strong knowledge of statistics and experimental design
  • Experience in designing and building data pipelines
  • Solid business acumen and experience in synthesizing complex analyses into interpretable content
  • A demonstrated ability to manage and deliver on multiple projects
  • A builder’s mindset with a willingness to question assumptions and conventional wisdom

Please mention No Whiteboard if you apply!
I'm a one-man team looking to improve tech interviews, and could use any support! 😄

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