Data Scientist

Stripe

8d

About The Position

Stripe's Data Science team collaborates closely with various departments to provide essential models, data products, and insights for informed decision-making and responsible growth. The team focuses on analyzing data, developing machine learning and statistical models, and conducting experiments to drive impact across product optimization (user needs, fraud prevention, charge flow optimization), business operations (forecasting, liquidity management, risk assessment), and go-to-market strategies (growth experiments, marketing investment optimization, sales process refinement, causal effect estimation). This role involves partnering with Product, Finance, Payments, Security, Risk, Growth, and Go-to-Market teams to optimize systems and leverage data for strategic business decisions. The core mission is to ensure company strategy, products, and user interactions effectively utilize rich data through techniques such as machine learning, statistical modeling, causal inference, optimization, experimentation, and analytics.

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
• Proficiency in SQL and a computing language such as Python or R
• Experience in working with cross-functional teams to deliver results
• Ability to communicate results clearly and a focus on driving impact
• A demonstrated ability to manage and deliver on multiple projects with a high attention to detail
• Strong business acumen and experience in synthesizing complex analyses into actionable recommendations
• Proficiency with AI tools to accelerate model development, analysis, and coding

Nice To Haves

• 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
• Experience designing, running, and analyzing complex experiments or leveraging causal inference designs
• A builder's mindset with a willingness to question assumptions and conventional wisdom
• Experience with distributed tools such as Spark, Hadoop, etc.
• A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

Responsibilities

• Partner with Product, Finance, Payments, Security, Risk, Growth, and Go-to-Market teams.
• Optimize systems and leverage data to make strategic business decisions.
• Ensure company strategy, products, and user interactions make smart use of our rich data.
• Utilize techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree