Data Scientist, Forecasting Platform

Seattle, New York, Remote

Applications have closed

Stripe

Stripe powers online and in-person payment processing and financial solutions for businesses of all sizes. Accept payments, send payouts, and automate financial processes with a suite of APIs and no-code tools.

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Stripe’s business is complex and growing, and forecasting its future is no easy feat. Our forecasting efforts are diverse, spanning different dimensions of our business (geographies, business types), variable time periods (early-stage vs late-stage users), and methodologies (traditional time series modeling, ML-based methods). We are looking for an experienced data scientist to work on the planning, implementation, and building of infrastructure that enables and automates forecasting across all of Stripe. If you are excited about time series modeling and motivated by having an impact on the business, we want to hear from you.

You will:

  • Plan, develop, and build a forecasting framework that can produce regular, accurate, responsive statistical forecasts to be used for company planning
  • Incorporate new statistical modeling and/or machine learning methods to improve forecast performance
  • Drive efforts around explanation of forecast trends, development of new accuracy metrics, and estimation of uncertainty
  • Bring in new methodology to improve forecast responsiveness to the macro-environment, such as COVID and other economic changes
  • Build ‘what-if’ analysis capabilities to allow business leaders to quantitatively encode and model their assumptions

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 or R and SQL
  • Strong knowledge of statistics and experimental design
  • Prior experience working with time series models
  • The ability to communicate results clearly and a focus on driving impact

Nice to haves:

  • Prior experience with data-distributed tools (Scalding, Spark, Hadoop, etc)
  • Prior experience writing or contributing to Python or R packages

 

Tags: Economics Engineering Hadoop Machine Learning PhD Python R Spark SQL Statistical modeling Statistics

Perks/benefits: Startup environment

Regions: Remote/Anywhere North America
Country: United States
Job stats:  56  5  0
Category: Data Science Jobs

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