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About the Role
Join the Fraud Data Science team to build and enhance models for Stripe's fraud detection and loss management systems. Collaborate with Fraud Engineering and Risk Operations to deploy models into production and leverage data to inform fraud strategy. Apply machine learning, statistical modeling, causal inference, optimization, and experimentation to critical risk challenges in global payments.
Responsibilities
- Build and improve models powering Stripe's fraud detection and loss management systems.
- Work closely with Fraud Engineering and Risk Operations to move models from research to production.
- Use data to surface insights that shape fraud strategy across the business.
- Apply supervised and unsupervised machine learning, statistical modeling, causal inference, optimization, and experimentation to risk problems.
Requirements
- PhD with 1-3 years, MS or MA with 2-6 years, or BS or BA with 4-8 years of data science or quantitative modeling experience.
- Experience with Fraud, Risk or Financial Crimes.
- Proficiency in SQL and a computing language such as Python or R.
- Experience working with cross-functional teams to deliver results.
- Ability to communicate results clearly and a focus on driving impact.
- Demonstrated ability to manage and deliver on multiple projects with high attention to detail.
- Strong business acumen and experience in synthesizing complex analyses into actionable recommendations.
- Proficiency with AI tools to accelerate model development, analysis, and coding.
- Strong knowledge and hands-on experience in machine learning, statistics, optimization, causal inference, and experimentation.
- Experience deploying models in production and adjusting model thresholds to improve performance.
- Experience designing, running, and analyzing complex experiments or leveraging causal inference designs.
- A builder's mindset with a willingness to question assumptions and conventional wisdom.
- Experience with distributed tools such as Spark, Hadoop, etc.
Skills
- SQL
- Python
- R
- AI tools
- Machine learning
- Statistics
- Optimization
- Causal inference
- Experimentation
- Spark
- Hadoop
Experience Level
- 1-3 years (PhD)
- 2-6 years (MS/MA)
- 4-8 years (BS/BA)
Education Level
- PhD
- MS
- MA
- BS
- BA
- Quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)
About the Company
- Stripe is a financial infrastructure platform for businesses.
- Millions of companies use Stripe to accept payments, grow revenue, and accelerate new business opportunities.
- Stripe's mission is to increase the GDP of the internet.