Data Scientist

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 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 at 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. Who You Are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply.

The preferred qualifications are a bonus, not a requirement. Minimum Requirements 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 machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation Experience working with cross‑functional teams to deliver results Ability to communicate results clearly and focus on driving impact A demonstrated ability to manage and deliver on multiple projects with high attention to detail Solid business acumen and experience in synthesizing complex analyses into actionable recommendations A builder’s mindset with a willingness to question assumptions and conventional wisdom Preferred Qualifications Experience deploying models in production and adjusting model thresholds to improve performance Experience designing, running, and analyzing complex experiments or leveraging causal inference designs Experience with distributed tools such as Spark, Hadoop, etc. A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research) In‑Office Expectations Office‑assigned roles in most locations are expected to spend at least 50% of the time in a given month in their local office or with users.

This may vary by role, team and location. For example, roles in the Stripe Delivery Center in Mexico City, Mexico, and Bengaluru, India work 100% from the office. Some teams have greater in‑office attendance requirements to support users and workflows.

The hiring manager will discuss the approach. Pay and Benefits The annual salary range for this role in the primary location is CA$172,500 – CA$258,700. This range may change by location.

For sales roles, the OTE range includes commissions and bonuses. The range is narrowed during the interview process based on experience, qualifications, and location. Benefits may include equity, company bonus or commissions, retirement plans, health benefits, and wellness stipends. #J-18808-Ljbffr