PhD Data Scientist Intern

5d5 days ago

Stripe

New York City, US · Internship · $90,000 – $120,000

About this role

Stripe is a financial infrastructure platform for businesses, used by millions of companies from largest enterprises to ambitious startups to accept payments, grow revenue, and accelerate opportunities. Our mission is to increase the GDP of the internet. The Data Science team partners with teams across Stripe to provide models, data products, and insights for responsible growth.

Data scientists analyze data, build machine learning and statistical models, and run experiments to influence products like fraud prevention, business forecasting, liquidity management, and go-to-market experiments. Interns work on meaningful initiatives with large datasets and analytical tools to understand users and improve products. Each project aligns with the team's roadmap and contributes to Stripe's mission.

Interns partner with Data Scientists, Analysts, and business teams in a collaborative environment. They receive a dedicated mentor and engage with industry experts on global commerce initiatives. The team handles broad work from user needs to risk quantification across Stripe.

The internship fosters technical expertise and personal development for a tech career. Interns present work to the Data Science team, partners, and fellow interns. It offers firsthand understanding of analytics in business strategy and results.

Requirements

Enrolled in a quantitative PhD program (e.g. Data Science, Statistics, Economics, Mathematics) expecting to graduate winter 2026 or spring/summer 2027
Experience with a scientific computing language (such as Python, R) and SQL
Passion for analyzing data and building machine learning and statistical models
Experience running experiments to drive impact
Familiarity with large datasets and analytical methodologies
Ability to work with causal inference and advanced analytics

Responsibilities

Partner closely with Data Scientists, Data Analysts, and business partners to drive business impact through rigorous analytical solutions
Apply machine learning, causal inference, or advanced analytics on large datasets to measure results, identify causal impact, and predict user or product performance
Influence business actions and strategy by developing actionable insights through metrics and dashboards
Drive the collection of new data and refinement of existing data sources
Learn quickly by asking great questions, working effectively with mentor and teammates, and communicating work status clearly
Present work to the Data Science team, partner teams, and fellow interns