Data Scientist, Connections
Seattle, New York, Remote (US)
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.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.
You will:
- 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
We’re looking for someone who has:
- 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
Nice to haves:
- Experience with tools for working with “big data” in a distributed fashion (Spark, Hadoop, etc.)
- Experience analyzing financial industry products
- Experience building ETL pipelines
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Banking Big Data Economics Engineering ETL Hadoop Machine Learning ML models PhD Pipelines Python R Spark SQL Statistics
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