Data Scientist, Link

Details

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. Stripe's mission is to increase the GDP of the internet.

About the Team

The Data Science team partners with teams across Stripe to ensure that users, products, and the business have the models, data products, and insights needed to make decisions and grow responsibly. The team analyzes data, builds machine learning and statistical models, and runs experiments to drive impact across product development, fraud prevention, charge-flow optimization, forecasting, liquidity management, risk quantification, growth experiments, marketing investment optimization, and sales-process refinement.

The Link Data Science team is the dedicated data science and analytics partner for Link, Stripe's one-click checkout product, which is trusted by more than 300 million users. The team is hiring data scientists to support two areas:

• Local Payment Methods: Enable consumers globally to pay with preferred local payment methods such as UPI and PIX. The role involves supporting additional payment methods, analyzing friction points, improving the product, and shaping consumer payment method preferences.
• Link Consumer Team: Support consumer-focused features including subscription management, multiple payment methods, rewards optimization, and an agentic AI wallet that enables a preferred AI model to transact without exposing payment credentials.

Responsibilities

• Work closely with a specific part of the business to optimize systems and leverage data for strategic decisions.
• Apply machine learning, statistical modeling, causal inference, optimization, experimentation, and analytics.
• Design, run, and analyze complex experiments.
• Use causal inference designs to generate actionable insights.
• Partner with cross-functional teams to deliver results.
• Deploy models in production and adjust model thresholds to improve performance.
• Analyze product friction and identify opportunities to improve Link and its payment experiences.

Requirements

Minimum Requirements

• PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience.
• 3+ years of experience in product analytics, experimentation, and causal inference.
• Experience designing, running, and analyzing complex experiments or leveraging causal inference designs.
• Proficiency in SQL and Python.
• Experience working with cross-functional teams to deliver results.
• Ability to communicate results clearly, with a focus on driving impact.
• Demonstrated ability to manage and deliver multiple projects with high attention to detail.
• Strong business acumen and experience synthesizing complex analyses into actionable recommendations.
• Proficiency with AI tools to accelerate model development, analysis, and coding.

Preferred Qualifications

• Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation.
• Experience deploying models in production and adjusting model thresholds to improve performance.
• A builder's mindset and willingness to question assumptions and conventional wisdom.
• Experience with distributed tools such as Spark and Hadoop.
• A PhD or MS in a quantitative field, such as statistics, engineering, mathematics, economics, quantitative finance, sciences, or operations research.