Data Scientist, Fraud

Job Description

We're looking for a Data Scientist to join the Fraud Data Science team at Stripe. In this role, you'll build and improve the models that power Stripe's fraud detection and loss management systems.

Responsibilities

• Build and improve models for fraud detection and loss management
• 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

Preferred Qualifications

• Strong knowledge and hands-on experience in several of the following areas: 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.
• A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)