Data Scientist - Data Science - F/H

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 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.

We’re looking for a variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth and Go-to-Market teams. You’ll work closely with a specific part of the business, playing a crucial role in optimizing our systems and leveraging data to make strategic business decisions. As Data Scientists as Stripe, it’s our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics.

If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

PhD + 3 years, MS/MA + 6 years or BS/BA 8 years of data science/quantitative modeling experience

Proficiency in SQL and a computing language such as Python or R

Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation

A demonstrated ability to manage and deliver on multiple projects with a high attention to detail

Solid business acumen and experience in synthesizing complex analyses into actionable recommendations

Experience deploying models in production and adjusting model thresholds to improve performance

A PhD or MS in a quantitative field (e.g., In-office expectations

Office-assigned Stripes in most of our locations are currently expected to spend at least 50% of the time in a given month in their local office or with users. For example, Stripes in our Bucharest, Romania site have an 80% in-office expectation, and those in Stripe Delivery Center roles in Mexico City, Mexico and Bengaluru, India work 100% from the office. Also, some teams have greater in-office attendance requirements, to appropriately support our users and workflows, which the hiring manager will discuss. This approach helps strike a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility when possible.

For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Benefits/additional compensation for this role may include: equity, company bonus or sales commissions/bonuses; retirement plans;