Data Scientist, Payments

About Stripe

Stripe serves as a financial infrastructure platform that supports businesses worldwide, from major enterprises to innovative startups, enabling them to accept payments, increase revenue, and seize new business opportunities. The company’s mission is to boost the GDP of the internet, offering a unique chance to impact the global economy significantly by working on crucial challenges.

About The Team

The Data Science team at Stripe collaborates closely with cross-functional groups to provide models, data products, and actionable insights that empower decision-making and sustainable growth. Their work spans optimizing product features, enhancing business outcomes, and improving go-to-market strategies through data-driven analytics, experimentation, and machine learning.

Role Overview

The Data Scientist will engage with Local Payment Methods (LPM) teams to analyze, expand, and optimize the LPM segment of Stripe’s business using data. Responsibilities include applying advanced methods like machine learning, statistical modeling, causal inference, and experimentation to inform strategic business choices.

Minimum Qualifications

• PhD, MSc, or MA with at least 2 years of experience in data science or quantitative modeling, or a BS/BA with 3 years of relevant experience
• Strong skills in SQL and programming languages such as Python or R
• Experience collaborating with cross-functional teams to produce results
• Ability to communicate findings clearly and focus on driving impact
• Proven ability to handle multiple projects with attention to detail
• Sound business insight with capability to convert complex analysis into practical recommendations
• Experience using AI tools to speed up model development, data analysis, and coding

Preferred Qualifications

• Expertise in areas such as machine learning, statistics, optimization, product analytics, causal inference, and experiment design
• Experience deploying models to production and tuning model thresholds for better outcomes
• Skill in designing and assessing sophisticated experiments or using causal inference techniques
• A mindset oriented toward building solutions and challenging existing assumptions
• Familiarity with distributed computing tools like Spark and Hadoop
• Educational background with a PhD or MSc in quantitative fields including Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, or Operations Research

In-office Work Expectations

Employees are generally expected to work at least 50% of their time onsite within the local office or with users. This ratio may differ based on role, team, and location. Certain teams or locations may require full on-site presence to better support users and workflows.

Compensation and Benefits

The salary for this position at the primary location ranges annually from €77,200 to €115,800, with variations depending on the candidate’s experience, qualifications, and place of employment. Benefits may comprise equity, bonuses, retirement plans, health coverage, and wellness stipends. Detailed compensation discussions will occur during interviews.