Senior Data Scientist

We are seeking a Lead Data Scientist to build, test, and deploy automated fraud detection systems that reduce payment fraud, chargebacks, and ecosystem exploits. You will deliver production-ready models, pipelines, and documentation while partnering closely with fraud operations.

Responsibilities

• Design automated fraud detection systems to mitigate payment fraud, chargebacks, and ecosystem exploits
• Build and deploy machine learning models to identify and prevent credit card fraud and chargebacks
• Implement real-time preventative purchase rule optimization to reduce risk while maintaining purchase flow performance
• Develop anomaly detection models to replace manual fraud analysis workflows
• Engineer and operate data pipelines that support production fraud detection and monitoring
• Deliver comprehensive technical documentation covering model architecture, pipelines, and detection logic
• Coordinate knowledge transfer and offboarding support to transition stabilized systems to internal team members
• Prioritize and deliver high-impact detection capabilities on an accelerated timeline ahead of major releases and sales events

Requirements

• 5+ years of data science experience with production machine learning systems
• 5+ years of Python experience for data analysis and model development
• 5+ years of experience in machine learning model development and deployment
• 3+ years of experience in fraud detection for payments or chargeback prevention
• Strong leadership skills to drive high-impact delivery and align stakeholders
• Strong project execution skills to deliver rapid rollouts ahead of major releases and sales events
• Strong applied ML skills including additive machine learning models and anomaly detection approaches
• Strong real-time data processing skills to support low-latency detection and prevention
• Strong analytical skills to translate fraud patterns into measurable detection logic
• Strong collaboration skills to partner with fraud operations and replace manual workflows
• Strong communication skills to produce clear technical documentation and knowledge transfer materials
• Upper-Intermediate English proficiency (B2)

Nice to have

• Databricks
• Anthropic Claude Code

Benefits

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn