Data Scientist, Enrichment

Data Scientist, Enrichment

Stripe builds the most powerful and flexible tools for running an internet business. We handle billions of dollars each year and enable millions of users around the world to scale faster and more efficiently by building their businesses on Stripe. More than half of US internet users have purchased something from a Stripe user in the past year.

With all this data, we’re looking for a talented data scientist to join the Data Science team to help us better understand our users, build better products, and optimize our operation. If you are data curious, excited about deriving insights from data, and motivated by having an impact on the business, we want to hear from you.

You will:

  • Help build Stripe’s Company Universe, an internal data product that comprises vast firmographic data as well as machine learning models
  • Incorporate new machine learning and/or statistical methods to create new predictive and classification models or improve existing models, such as our Customer Lifetime Value and Startup Identification models
  • Partner with data and software engineers to design the data architecture and core abstractions to integrate, and harmonize company information from multiple external sources, Stripe user-facing surfaces, and internal systems
  • Lead data science efforts to define our customer segmentation using Company Universe data
  • Evaluate and integrate new data sources to expand the international scope of our data
  • Empower Stripe’s Sales and Marketing teams to better understand and action their leads, Risk and - Operations teams to offer world-class personalized experiences, and many more high-value use cases

We’re looking for someone who has:

  • 5+ years experience working with and analyzing large data sets to solve problems
  • A PhD or MS in a quantitative field (e.g., Statistics, Sciences, Economics, Engineering, CS)
  • Expert knowledge of Python and SQL
  • Prior experience with distributed tools (Scalding, Spark, Hadoop, etc.)
  • Strong knowledge of machine learning and statistics
  • Experience working with multiple cross-functional teams to deliver results
  • The ability to communicate results clearly and a focus on driving impact
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