PhD Data Scientist, Intern

Stripe; San Francisco (CA); On-site; USD 147,000 - 180,000; Full time

Job summary

Stripe is seeking a Data Science intern for its Sales/ Fraud data domains in San Francisco. You will work across the data stack, owning problems end to end with mentorship. Build metrics, data pipelines, dashboards, and reports to inform business decisions and drive responsible growth.

You’ll learn from a rigorous, interdisciplinary team while contributing to models and experiments used to protect Stripe and its users. Prior PhD coursework and SQL/Python fluency are expected.

Qualifications

• Enrolled in a quantitative PhD program with expected graduation in December 2027 or spring/summer 2028.
• Experience with SQL and a scientific computing language (Python, R).
• Proficiency with AI tools to accelerate model development, analysis, and coding.
• Experience collaborating with multidisciplinary stakeholders in a team environment.
• Experience writing and debugging data pipelines.
• Ability to learn new systems and form an understanding with mentorship.

Responsibilities

• Apply probability distributions, statistical inference, and hypothesis testing to quantify outcomes.
• Use Python or R for data analysis, processing, visualizations, and modeling.
• Build, train, and evaluate predictive models for regression/classification tasks.
• Model temporal dependencies and time-series components for forecasts.
• Identify patterns in unlabeled data and deploy models to production.
• Design, run, and analyze experiments and causal inference designs.
• Use SQL and Spark to transform and analyze large datasets.
• Communicate status and collaborate effectively with mentors and teammates.
• Present findings to the Data Science team and partner teams.

Skills

SQL

Python

R

AI tools

Cross-functional collaboration

Education

Quantitative PhD program enrollment

Tools

Spark

Python

R

Job description

About Stripe

Stripe is a technology company focused on improving the conditions for economic growth and prosperity. We build programmable financial infrastructure, rethinking from first principles how financial services should work, to make it easier and cheaper for any business to start and scale. More than 10 million businesses build on Stripe, spanning the economic frontier—from solo founders to established enterprises—united by a practical focus on growth. The most ambitious companies in the world use Stripe as core infrastructure to grow faster. They process trillions of dollars a year on Stripe, equivalent to around 1.6% of global GDP. While economic growth makes everyone better off, open markets also enable greater variety. When any business can easily serve a global customer base, the quality and diversity of products in the world increase, and craft and creativity are unleashed into the smallest niches. Our own growth is wholly contingent on the success of the businesses building on Stripe. We therefore invest back into our technology at an unusual rate. We make upgrades to our products every single day to deliver compounding gains to our customers. We maintain some of the most reliable APIs on the internet. We build entirely new pieces of financial infrastructure to enable new ideas. And our significant advances in risk and fraud infrastructure over many years are making the internet economy safer and more accessible.

Who we are

About Stripe

Stripe is a technology company focused on improving the conditions for economic growth and prosperity. We build programmable financial infrastructure, rethinking from first principles how financial services should work, to make it easier and cheaper for any business to start and scale. More than 10 million businesses build on Stripe, spanning the economic frontier—from solo founders to established enterprises—united by a practical focus on growth. The most ambitious companies in the world use Stripe as core infrastructure to grow faster. They process trillions of dollars a year on Stripe, equivalent to around 1.6% of global GDP. While economic growth makes everyone better off, open markets also enable greater variety. When any business can easily serve a global customer base, the quality and diversity of products in the world increase, and craft and creativity are unleashed into the smallest niches. Our own growth is wholly contingent on the success of the businesses building on Stripe. We therefore invest back into our technology at an unusual rate. We make upgrades to our products every single day to deliver compounding gains to our customers. We maintain some of the most reliable APIs on the internet. We build entirely new pieces of financial infrastructure to enable new ideas. And our significant advances in risk and fraud infrastructure over many years are making the internet economy safer and more accessible. Though people at Stripe don’t tend to take themselves seriously, Stripe is a fairly serious place: our customers are depending on us for their livelihoods. We admire ambition, intensity, curiosity, humility, and rigor. The most effective people become knowledgeable about many domains besides their own. Any company is an applied exercise in understanding some aspect of society or the market. In working with so many (especially the new and innovative ones), we think that Stripe is one of the very best places to learn about how the world works.

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 Fraud, Losses, and Financial Crime Data Science team builds the models and data products that protect Stripe and its users from fraud, account takeover, and financial crime. We own the full fraud and loss modeling stack - from account takeover detection and card fraud classification to merchant-level loss estimation, unsupervised anomaly detection, and financial crime risk modeling. We partner with Fraud Engineering, Financial Crimes Engineering, and Risk Operations to bring these systems into production and ensure they have measurable impact on Stripe's financial integrity and user trust.

What you’ll do

As an intern at Stripe you’ll work on projects across our stack that directly impact the way millions of businesses operate. You’ll own problems end to end with the support of your manager and teammates. It’s an opportunity to work alongside some of the most creative and technically rigorous data analysts and scientists in the industry. You'll partner 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. You'll work closely with partners to extract insights from the rich and complex data at Stripe. You'll build metrics, scalable data pipelines, dashboards, and reports to inform and run the business. You'll deliver actionable business recommendations through analyses and data storytelling. Our internship program is competitive and the expectations are high.

Responsibilities

• Applying probability distributions, statistical inference, and hypothesis testing to quantify uncertainty and evaluate business outcomes
• Using Python or R for data analysis, data processing, visualizations, statistical modeling, machine learning, predictive analytics, automation, and implementing causal inference and experimental analyses
• Building, training, and evaluating predictive models across regression and classification tasks for bias-variance trade-offs and model selection
• Modeling temporal dependencies, seasonality, and trend decomposition to generate and evaluate time-series predictions
• Identifying structural patterns, clusters, and outliers in unlabeled data
• Deploying models in production and adjusting model thresholds to improve performance
• Designing, running, and analyzing complex experiments and leveraging causal inference designs
• Using SQL and Spark to create, transform, and analyze large datasets
• Learn quickly by asking great questions, finding how to work with your mentor and teammates effectively, and communicating the status of your work clearly
• Present your work to the Data Science team, partner teams, and fellow interns.

Who you are

• Ambitious builder: You’re energized by building solutions without clear precedent and solving problems with far-reaching consequences. Successful Stripes are deeply curious, and prefer the joy of discovery to the comfort of certainty.
• Rigorous thinker: You appreciate that things worth doing are rarely simple. You enjoy working on problems that have never been tackled before.
• Adaptable problem solver: You adapt quickly and treat obstacles as opportunities. At Stripe we embrace kindness while encouraging Stripes to take measured risks and act boldly, even in the absence of consensus.

Minimum Requirements

• Enrolled in a quantitative PhD program (e.g. Data Science, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in December 2027 or spring/summer 2028
• Experience with SQL and a scientific computing language (such as Python, R, etc.)
• Proficiency with AI tools to accelerate model development, analysis, and coding
• Experience communicating and collaborating with multidisciplinary stakeholders in a team environment

Preferred Qualifications

• Experience writing and debugging data pipelines
• Demonstrated ability to evaluate and receive feedback from mentors, peers, and stakeholders via experience from previous internships or other multi-person projects
• Ability to learn new systems and form an understanding of those systems, through independent research and working with a mentor and subject matter experts

In-office expectations

Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. This expectation may vary depending on role, team and location. For example, Stripes in Stripe Delivery Center roles in Mexico City, Mexico, Bengaluru, India, and Dublin, Ireland work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible.

Pay and benefits

The annual US base salary range for this role is $163,800 - $163,800. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.