Data Scientist - Global Growth

About Stripe

Stripe is a leading financial infrastructure company enabling millions of enterprises and startups globally to accept payments, expand revenue, and accelerate business growth. Our central mission is to increase internet GDP, creating vast opportunities for impactful work in the global economy.

Team Overview

The Data Science group collaborates across various units within Stripe to provide models, data products, and insights essential for informed decisions and responsible growth. Our data scientists specialize in analytical data interpretation, machine learning and statistical model development, and experimental design to foster impact. Our interdisciplinary work addresses product functionality (like user needs, fraud prevention, charge flow optimization), business operations (forecasting, liquidity management, risk analysis), and go-to-market functions (designing growth experiments, marketing investment optimization, sales refinement, causal effect analysis).

Role Responsibilities

As a Data Scientist focused on Global Growth, you will partner closely with the global growth teams to design and implement experiments, reveal enhancement opportunities across stripe.com and the dashboard, and support worldwide business onboarding. Key responsibilities include optimizing the self-service user conversion funnel, ensuring high-quality onboarding experiences, and leveraging data science techniques such as machine learning, statistical modeling, causal inference, optimization, and experimentation to influence company strategy and user interaction.

Candidate Profile

Applicants should meet the following minimal qualifications, with additional preferred skills seen as advantageous but not mandatory.

Minimum Qualifications

• Bachelor's degree plus eight years, Master's plus six years, or PhD plus three years in data science or quantitative modeling.
• Proficient in SQL and a programming language such as Python or R.
• Experience collaborating with cross-functional teams to achieve results.
• Strong communication skills and a focus on actionable impacts.
• Proven ability to manage multiple projects meticulously.
• Solid business understanding and aptitude for translating complex analyses into strategic recommendations.
• Familiarity with AI tools to expedite model building, data analysis, and coding.

Preferred Qualifications

• Expertise in areas including but not limited to machine learning, statistics, optimization, product analytics, causal inference, and experimentation.
• Hands-on experience deploying models in production environments and optimizing model thresholds.
• Experience designing, conducting, and interpreting complex experiments, particularly those utilizing causal inference frameworks.
• A problem-solving, builder mentality willing to question norms and assumptions.
• Experience working with distributed computing platforms like Spark or Hadoop.
• Advanced degrees such as MSc or PhD in quantitative fields including Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, or Operations Research.

Workplace Attendance

Employees assigned to an office location are generally expected to spend at least half their working time monthly on-site, balancing in-person collaboration and flexible arrangements. Some teams or locations may have stricter in-office requirements tailored to workflow and user support needs.

Compensation and Benefits

The anticipated salary for this position in Singapore ranges from SGD 172,000 to SGD 258,000 annually, adjustable by location and candidate factors. Sales roles have an On Target Earnings range combining base and bonus compensation. Additional benefits may include equity, company bonuses or sales commissions, health plans, retirement options, and wellness stipends. Specifics vary and will be addressed during the interview process.

Additional Information

We encourage applicants with diverse backgrounds and perspectives who demonstrate passion, integrity, and rigorous thinking to apply even if their experience does not exactly match the listed criteria. Our inclusive culture embraces challenge and innovation.