Data Scientist, Forecasting
Stripe (View all Jobs)
US-Chicago, US-NYC, US-Seattle, USA (Remote)
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
Who we are
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
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.
- 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 macroenvironment, such as COVID and other economic changes
- Build ‘what-if’ analysis capabilities to allow business leaders to quantitatively encode and model their assumptions
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.
- 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
- 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
- A demonstrated ability to manage and deliver on multiple projects
- A builder’s mindset with a willingness to question assumptions and conventional wisdom
- Prior experience with data-distributed tools (Scalding, Spark, Hadoop, etc)
- Prior experience writing or contributing to Python packages
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