Data Scientist - Payments

About Stripe

Stripe serves as a financial infrastructure platform empowering millions of companies of all sizes to accept payments, increase revenue, and unlock new business opportunities. Our mission is to expand the economy of the internet globally, offering a remarkable opportunity to contribute to impactful work that reaches worldwide.

About The Team

The Data Science team collaborates extensively across Stripe to provide models, data products, and insights that enable informed decision-making and responsible growth. The team's efforts impact product design, business strategy, and go-to-market dynamics, applying diverse techniques such as machine learning, experimentation, optimization, and causal inference.

Role Overview

We are seeking a Data Scientist to collaborate with the Local Payment Methods (LPM) engineering and product teams. This role focuses on understanding, expanding, and improving the LPM sector through strategic data analysis and modeling to drive effective business decisions.

Responsibilities

• Leverage data science techniques including machine learning, statistical modeling, experimentation, and optimization to support product and business strategy.
• Collaborate closely with cross-functional teams to influence product development and business outcomes.
• Develop and assess experiments and models to optimize payment flows and user experience within Local Payment Methods.

Minimum Qualifications

• PhD, MSc, or MA with at least 2 years, or BS or BA with at least 3 years of relevant experience in data science or quantitative modeling.
• Expertise in SQL and a programming language such as Python or R.
• Experience working across teams to deliver measurable results with clear communication of insights.
• Demonstrated capability to manage multiple projects with meticulous attention to detail.
• Strong business insight with the ability to translate complex analyses into actionable strategies.
• Proficiency in utilizing AI tools to enhance data modeling, analysis, and coding efficiency.

Preferred Qualifications

• In-depth knowledge and practical experience with machine learning, statistics, optimization, product analytics, causal inference, and experimentation.
• Track record deploying models in production environments and fine-tuning model parameters.
• Experience designing and interpreting sophisticated experiments and causal inference methodologies.
• Innovative problem-solving mindset with the willingness to challenge conventional assumptions.
• Familiarity with distributed computing tools such as Spark or Hadoop.
• Advanced degrees (PhD or MSc) in quantitative disciplines like Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, or Operations Research.

In-Office Expectations

Employees in most Stripe offices are expected to spend a minimum of 50% of their working time monthly onsite, with some roles, including those in Dublin, requiring full-time office presence. In-office attendance requirements may vary by team and role to best support collaboration and workflows.

Compensation and Benefits

The annual salary range for this position in Dublin is €77,200 to €115,800. The precise salary will be determined by factors such as experience and location and may include equity, bonuses, retirement plans, health benefits, and wellness stipends. Additional pay components and benefits details will be discussed during the interview process.