PhD Data Scientist, Intern
- Your creative and detail-oriented nature helps you approach data analysis with a fresh perspective, noticing subtle patterns that others may miss.
- You value authenticity and will connect with Stripe’s mission, which can give your work deeper meaning and motivation beyond technical metrics.
- Your flexibility allows you to adapt to changing project needs and learn new tools as required, which fits the dynamic internship environment.
- The structured, deadline-driven nature of the internship may feel restrictive, as you prefer to work at your own pace and follow your inspiration.
- Collaborating with a large team and presenting findings can be draining, since you are more introverted and prefer to express insights through your work rather than verbal discussions.
Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
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 work is broad and varied, influencing how our products work (e.g. understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background.
What you’ll do
About the internship experience
Our internship program provides the opportunity to work on meaningful business initiatives that will grow the GDP of the internet. Through the internship, you will work with many systems and technologies, gain experience in working with large datasets and analytical methodologies/tools to help us better understand our users and build better products.
Each intern has a dedicated mentor, and every intern project is part of the team's roadmap that will directly contribute to Stripe's mission. As you collaborate with industry experts on initiatives that expand global commerce, you will develop a strong first-hand understanding of the role analytics plays in steering business strategy and results.
We're not just focused on your immediate contributions; we're invested in your growth. Stripe sees this internship as an opportunity to grow your technical expertise and facilitate personal development, preparing you for a career in the tech industry.
Responsibilities
You will:
- 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: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict the future performance of users or products, to drive business success
- Influence business actions and strategy by developing actionable insights through metrics and dashboards
- Drive the collection of new data and the refinement of existing data sources
- 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
Minimum requirements
We’re looking for someone who has:
- Enrolled in a quantitative PhD program (e.g. Data Science, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in winter 2026 or spring/summer 2027
- Experience with a scientific computing language (such as Python, R, etc) and SQL. We believe new programming languages can be learned if the fundamentals and general knowledge are present!
- Knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
- Experience communicating and collaborating with multidisciplinary stakeholders in a team environment
Preferred qualifications
You also likely 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 a mentor and subject matter experts
Best personality fits for this role
Your strategic mindset helps you design and execute powerful data-driven solutions for complex business problems, aligning with the role’s focus on influencing strategy through analytics.
Read the INTJ career guide →Your natural curiosity and love for theoretical models make you excellent at exploring complex analytical problems in machine learning, statistics, and causal inference required by the role.
Read the INTP career guide →Your innovative, big-picture thinking helps you generate creative approaches to measuring causal impact and predicting outcomes, matching the role’s need for advanced analytical solutions.
Read the ENTP career guide →