Payments Data Scientist

Stripe (View all Jobs)

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

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


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

R, SQL, 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

Payments are the core of Stripe’s business, and the groups and teams within Payments are broadly responsible for processing and moving funds at a huge scale.

Stripe’s goal is to make payments dead simple for our users. Internally, we operate a complex network of systems which interact with all parts of the financial system. We build infrastructure for charging credit cards (or other payment methods, like bank transfers or Alipay), integrations with our banking partners to send transfers to our users across the globe, systems that collect Stripe’s revenue and estimate cost, and more. Collectively, these systems power all payments products at Stripe, and we’re looking for talented Data Scientists to come help us use data to understand and optimize these complex processes and serve our users’ needs. Data Scientists at Stripe employ the full toolbox in order to advance our mission of building world-leading financial products and infrastructure, from experiments and causal inference, to working with our partner teams to rigorously define and forecast metrics, and developing and deploying ML models to solve customer needs. If this sounds exciting, we hope you will join us!

What you’ll do

  • Partner closely with Product, Engineering, UX Research, Marketing, Sales, Finance and Data Science teams to shape product strategy using rigorous scientific solutions
  • Apply statistical, machine learning and econometric models on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict future performance of users or products
  • Design, analyze, and interpret the results of experiments
  • Design, implement and launch innovative data science solutions to empower data-driven decisions and products at scale
  • Drive the collection of new data and the refinement of existing data sources
  • Create analyses that tell a story focused on insights, not just data

Who you are

  • 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, Engineering, Natural Sciences, Operations Research) 
  • Expert knowledge of a scientific computing language (such as R or Python) and SQL 
  • Strong knowledge of statistics, machine learning and optimization
  • Demonstrated track record of identifying, scoping and leading complex data science projects with cross-functional partners and high business impact 
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner

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


Get weekly alerts of new jobs from companies not using whiteboard interviews!