Data Science Manager, Payment Performance and Fraud
US-Chicago, US-New York City, US-Seattle, US- SF, USA (Remote)
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.Who we are
About Stripe
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
The Payment Intelligence group is responsible for optimizing each of the billions of dollars of transactions processed by Stripe each year on behalf of our users, in order to maximize successful transactions while minimizing payment costs and fraud. We own products like Radar, Adaptive Acceptance, and Chargeback Protection from end to end and work across the technical stack: from machine learning over our users’ data, to integrating ML intelligence and serving real-time predictions as part of Stripe’s payment infrastructure, to building user-facing product surfaces like dashboards and controls. We need your help in building out a culture of rigorous measurement, experimentation, and optimization.
What you’ll do
At Stripe, data science managers grow teams and inspire them to rigorous work that shapes our decisions and products. We’re looking for an experienced data science manager to lead our team supporting Payment Intelligence.
Responsibilities
- Lead a team of data scientists and analysts to:
- Define and measure key outcome metrics for our products + systems.
- Design and analyze experiments to improve the optimization systems at Stripe - ranging from products spanning fraud, authorization rates, and user costs.
- Apply statistical methods, causal inference, and predictive modeling to inform product decisions and optimize our products and systems.
- Build new (and expand existing) machine learning frameworks (which currently span Experimentation, Multi-Armed Bandits, Regression Trees, and Deep Learning) in order to stop fraud and optimize payments.
- Partner closely with product and engineering teams to identify and prioritize the most important data science projects
- Recruit great data scientists and analysts, in collaboration with Stripe’s recruiting team
- Develop data scientists and analysts on the team, helping them advance in their careers, providing them with continuous feedback
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.
Minimum requirements
- 5+ years of data science experience; 2+ years of management experience
- A PhD or MS in a quantitative field (e.g., Statistics, Economics, Sciences, Mathematics, Engineering)
- Expert knowledge of a scientific computing language (such as R or Python) and SQL
- Strong knowledge of statistics and experimental design
- Ability to communicate results clearly and a focus on driving impact
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Causal inference Deep Learning Economics Engineering Machine Learning Mathematics PhD Predictive modeling Python R Radar SQL Statistics
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