Data Scientist

Job summary

Data scientists will partner with cross-functional teams to build machine learning models, statistical models, and data products to drive strategic business decisions. They are responsible for analyzing complex data to optimize systems, prevent fraud, and quantify risk exposure across the organization.

Job 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. 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 Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you'll do We're looking for a variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth, and Go-to-Market teams. You'll work closely with a specific part of the business, playing a crucial role in optimizing our systems and leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. 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 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 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 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)

What you’ll do

Data scientists will partner with cross-functional teams to build machine learning models, statistical models, and data products to drive strategic business decisions. They are responsible for analyzing complex data to optimize systems, prevent fraud, and quantify risk exposure across the organization.

Requirements

Candidates must have a PhD with 3+ years, MS with 6+ years, or BS with 8+ years of quantitative modeling experience. Proficiency in SQL and a programming language like Python or R is required, along with strong communication and cross-functional collaboration skills.

Listed skills

• SQL · Preferred
• Data analysis · Preferred
• Risk Management · Preferred
• Machine learning · Preferred
• Python · Preferred
• Forecasting · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• SQL
• Python
• R
• Machine learning
• Statistical modeling
• Causal inference
• Optimization
• Experimentation
• Data analysis
• Product analytics
• Forecasting
• Risk management
• Distributed tools
• Spark
• Hadoop
• Business acumen
• Liquidity Management
• Go-to-Market Strategy
• Product Analytics
• Quantitative Modeling
• Security Risk
• Operations Research
• Data Analysis
• Business Acumen
• Investments
• Causal Inference
• Communication
• Data Modeling
• Mathematical Finance
• Economics
• Finance
• Sales
• R (Programming Language)
• Apache Hadoop
• Marketing
• Python (Programming Language)
• Machine Learning
• Mathematics
• SQL (Programming Language)
• Statistical Modeling
• Statistics
• Business Strategies
• Data Science
• Detail Oriented

Job areas

• Data & Analytics
• Technology
• Software
• Finance & Accounting
• Science & Research
• Data Scientist
• Systems Analysts
• Data Scientists