PhD Data Scientist Intern: Build ML models & insights

Stripe; Toronto (OH); On-site; USD 34,000 - 48,000; Full time

Job summary

Stripe is seeking a data science intern to work across our fraud, loss, and financial crime data science stack, building models and data products that inform decisions and grow responsibly. You’ll develop metrics, data pipelines, dashboards, and reports; collaborate with cross-functional teams; apply ML and statistical methods on large-scale data; gain hands-on experience in production environments.

The internship is competitive and demanding, offering mentorship and opportunities to contribute

Qualifications

• PhD student pursuing Data Science/Statistics/Math with expected graduate date 2027/2028.
• 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

Responsibilities

• Apply probability distributions, statistical inference, and hypothesis testing to quantify uncertainty and evaluate outcomes.
• Use Python or R for data analysis, processing, visualizations, modeling, ML, and experiments.
• Build, train, and evaluate predictive models for regression and classification tasks.
• Model temporal dependencies, seasonality, and trend decomposition for time-series forecasts.
• Identify patterns, clusters, and outliers in unlabeled data.
• Deploy models in production and adjust thresholds to improve performance.
• Design, run, and analyze complex experiments using causal inference.
• Use SQL and Spark to analyze large datasets.
• Communicate status and results clearly with mentors and teams.
• Present work to Data Science team and stakeholders

Skills

SQL

Python

R

AI tools

Education

PhD student in quantitative field

Tools

Spark

Job description

Stripe is seeking a data science intern to work across our fraud, loss, and financial crime data science stack, building models and data products that inform decisions and grow responsibly. You’ll develop metrics, data pipelines, dashboards, and reports; collaborate with cross-functional teams; apply ML and statistical methods on large-scale data; gain hands-on experience in production environments.

The internship is competitive and demanding, offering mentorship and opportunities to contribute