Data Scientist, Payments

About Stripe

Stripe provides a comprehensive financial infrastructure platform enabling millions of businesses worldwide—ranging from global enterprises to innovative startups—to manage payments, increase revenue, and explore new business avenues. Our mission is to expand the economic output of the internet, a goal that presents a significant workload and extraordinary career opportunities.

Team Overview

The Data Science team at Stripe collaborates closely with multiple departments to equip users, products, and the company with robust models, data products, and actionable insights facilitating well-informed decisions and responsible growth. The scope is vast, affecting product enhancement, fraud prevention, business forecasting, liquidity management, risk quantification, marketing optimization, sales improvement, and more. We have diverse Data Science roles and will match you to the team that best suits your expertise.

Role Responsibilities

As a Data Scientist working alongside the Local Payment Methods (LPM) engineering and product teams, your primary focus will be to analyze, expand, and optimize LPM business operations utilizing data to guide strategic choices. The role involves applying machine learning, statistical modeling, causal inference, optimization, experiments, and analytics to enhance company strategy, product development, and user experience.

Requirements

• Holders of a PhD, MSc, or MA with at least 2 years of experience in data science or quantitative modeling, or a BS or BA supplemented by 3 years of relevant experience.
• Proficient in SQL and at least one programming language such as Python or R.
• Experienced in collaborating with cross-functional teams to achieve impactful outcomes.
• Strong communication skills with an emphasis on delivering clear, impactful results.
• Capability to handle multiple projects simultaneously while maintaining meticulous attention to detail.
• Solid business insight with the aptitude to translate complex analyses into practical recommendations.
• Familiarity with AI tools that expedite model creation, data analysis, and programming tasks.

Preferred Qualifications

• Substantial experience in areas including machine learning, statistics, optimization, product analytics, causal inference, and experimental design.
• Hands-on expertise deploying models into production and fine-tuning thresholds to enhance model efficacy.
• Proven ability to design, execute, and interpret sophisticated experiments or employ causal inference methodologies.
• A builder's mindset characterized by questioning assumptions and conventional approaches.
• Experience with distributed computing tools like Spark and Hadoop.
• Advanced degrees (PhD or MSc) in quantitative disciplines such as Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, or Operations Research.

Work Arrangement

Employees assigned to an office are expected to spend at least half of their working time each month onsite or engaging directly with users. Specific expectations may vary by role, team, and location; for instance, roles at the Stripe Delivery Center in Dublin require full-time office presence. Managers will discuss attendance needs to balance collaboration, learning, and flexibility.

Compensation and Benefits

The base annual salary for this role in Dublin is between €77,200 and €115,800, with possible variations depending on your location and career level. Sales roles have ranges inclusive of base salary plus commissions or bonuses. Compensation details, including equity, bonuses, retirement plans, health benefits, and wellness stipends, will be further discussed during interviews and may differ by location.

Additional Information

We encourage applicants whose experiences may not exactly align with the job description to apply, valuing diverse perspectives and rigorous thinkers who challenge assumptions. We look forward to your application.