About this role
The Fraud, Losses, and Financial Crime Data Science team at Stripe builds the models and data products that protect the platform and its users from fraud, account takeover, and financial crime. Working within this group, interns take ownership of end-to-end problems across the stack, developing machine learning models and data products that directly impact how millions of businesses operate globally.
This role exists to bring rigorous statistical methods and predictive modeling to bear on complex financial security challenges, collaborating closely with engineering and risk operations partners. Ideal candidates are quantitative PhD students who enjoy deep technical discovery, thrive when solving ambiguous problems without clear precedent, and appreciate the responsibility of maintaining financial integrity and user trust at scale.
What you will do
- Apply probability distributions, statistical inference, and hypothesis testing to quantify uncertainty and evaluate business outcomes.
- Use Python or R for data analysis, statistical modeling, machine learning, predictive analytics, and causal inference.
- Build, train, and evaluate predictive models across regression and classification tasks while managing bias-variance trade-offs.
- Model temporal dependencies and trend decomposition to generate and evaluate time-series predictions.
- Identify structural patterns, clusters, and outliers in unlabeled data.
- Deploy models in production and adjust model thresholds to improve performance.
- Design, run, and analyze complex experiments while leveraging causal inference designs.
- Use SQL and Spark to create, transform, and analyze large datasets.
What you need
- Enrolled in a quantitative PhD program such as Data Science, Statistics, Economics, or Mathematics with expected graduation in December 2027 or spring/summer 2028.
- Experience with SQL and a scientific computing language like Python or R.
- Proficiency with AI tools to accelerate model development, analysis, and coding.
- Experience communicating and collaborating with multidisciplinary stakeholders in a team environment.
Nice to have
- 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 mentors and subject matter experts
Skills and tech stack
Questions candidates ask
What team will I be working with?
You will be working with the Fraud, Losses, and Financial Crime Data Science team, which builds the models and data products that protect Stripe and its users from fraud, account takeover, and financial crime.
What kind of projects will I own during the internship?
As an intern at Stripe, you will work on projects across our stack that directly impact the way millions of businesses operate, owning problems end to end with the support of your manager and teammates.
What qualifications are required to apply?
Candidates must be enrolled in a quantitative PhD program like Data Science, Statistics, Economics, or Mathematics with the expectation of graduating in December 2027 or spring/summer 2028, and bring experience with SQL, Python or R, and AI development tools.