This listing doesn't post a salary. Most similar roles pay
$126,800–$197,250.
Based on 240 similar postings.
Employer
About Stripe
Stripe is a financial infrastructure platform for internet businesses, providing payment processing, billing, fraud prevention, and banking-as-a-service APIs to businesses of all sizes globally. Industry: Payments Infrastructure & Financial Technology
Stripe currently has
99 open roles
on FindRole.
Listed pay typically runs
$203,600–$288,000
across 96 roles with salary data.
The PhD Data Scientist, Intern joins the Fraud, Losses, and Financial Crime Data Science team to build models and data products that protect users from fraud, account takeover, and financial crime. This role involves owning projects end-to-end, including building metrics, scalable data pipelines, dashboards, and reports to inform business decisions. You will perform statistical inference, hypothesis testing, and causal inference while developing predictive models for regression and classification tasks. The work involves modeling temporal dependencies, identifying patterns in unlabeled data, and deploying models into production. To succeed, you must utilize Python or R for analysis and modeling, along with SQL and Spark to process large datasets. You will also leverage AI tools to accelerate development while collaborating with multidisciplinary stakeholders to provide actionable insights regarding financial integrity and risk management across the platform's infrastructure.
What does a Data Scientist earn in New York?
Median $173200 from 35 postings across 15 companies.
Build, train, and evaluate predictive models for regression and classification tasks.
Use Python or R to perform statistical modeling, machine learning, and predictive analytics.
Design, run, and analyze complex experiments using causal inference designs.
Use SQL and Spark to create, transform, and analyze large datasets.
Develop scalable data pipelines, dashboards, and reports to inform business decisions.
Identify structural patterns, clusters, and outliers in unlabeled data.
Model temporal dependencies and seasonality to generate time-series predictions.
Deliver actionable business recommendations through data storytelling and presentations.
What we're looking for
Enrolled in a quantitative PhD program (e.g., Data Science, Statistics, Economics, Mathematics) graduating between December 2027 and summer 2028.
Experience with SQL and a scientific computing language such as 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.
Experience writing and debugging data pipelines (preferred).
Demonstrated ability to evaluate and receive feedback from mentors, peers, and stakeholders via previous internships or multi-person projects (preferred).
Ability to learn new systems through independent research and working with mentors and subject matter experts (preferred).