Data Scientist, Banking as a Service
Stripe (View all Jobs)
Seattle, New York, Remote (US)
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, ETL, Python
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
Software and Banking DS supports Stripe’s innovative and rapidly growing SaaS and BaaS products such as Invoicing, Billing, Capital, Issuing, Treasury, and more. We’re looking for talented data scientists to join our team to help us better understand our users. Through metrics, models, and insights, our work enables Stripe to support more users, new financial products, and new market segments. If you are an expert working with data to empower product strategy and forecast performance and excited to apply your experience to build new financial products, we want to hear from you.
What you’ll do
- Work closely with product, business, and engineering teams to conduct analyses and develop machine learning models to support new products
- Design forecast methods and marketing strategy
- Design, analyze, and interpret the results of experiments of different product strategies
- Apply statistical and analytical approaches on large datasets to measure results and outcomes of our current models and product strategies
- Drive the collection of new data and the refinement of existing data sources
Who you are
We’re looking for someone who is an expert when working with data to empower product strategy and forecast performance and excited to apply your experience to build new financial products, we want to hear from you.
- 5+ years experience working with large datasets to solve business problems, including 3+ years developing machine learning or statistical models
- Proficiency working with a scientific computing language (such as R or Python) and SQL
- Extensive experience and passion for product analytics and experimental design
- Strong knowledge of time series, statistics, and machine learning
- A PhD or MS in a quantitative field (e.g. Engineering, Statistics, Economics, Natural Sciences)
- Strong communication and presentation skills
- Experience with tools for working with “big data” in a distributed fashion (Spark, Hadoop, etc.)
- Experience analyzing financial industry products
- Experience building ETL pipelines
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