Senior Data Scientist

We are seeking a Senior Data Scientist to build, test, and deploy automated fraud detection systems that reduce payment fraud, chargebacks, and ecosystem exploits. You will partner with fraud operations to automate analysis, optimize preventative purchase rules in real time, and deliver production-ready models with clear documentation.

Responsibilities

• Design machine learning models to detect and prevent credit card fraud and chargebacks
• Build automated anomaly detection to replace manual fraud analysis workflows
• Deploy real-time fraud detection pipelines that support preventative purchase rule optimization
• Accelerate delivery of new detection capabilities ahead of major releases and sales events
• Validate model performance with robust testing and monitoring to control risk and accuracy
• Document model architecture, data pipelines, and detection logic for operational use
• Transfer knowledge and support offboarding to transition stabilized systems to internal teams
  
  

• 3+ years of experience in data science roles focused on fraud detection or risk analytics
• 3+ years of experience developing and deploying machine learning models in production environments
• 3+ years of experience using Python for model development and data processing
• Strong stakeholder collaboration skills for partnering with fraud operations and analytics teams
• Proven delivery ownership for rapid, high-impact rollouts under time-sensitive milestones
• Solid knowledge of real-time data processing concepts and low-latency detection needs
• Hands-on experience with AI solution engineering from prototype to operational deployment
• Advanced understanding of additive machine learning models and their use in anomaly detection
• Strong analytical skills to evaluate model performance and manage false positives/negatives
• Strong communication skills for technical documentation and knowledge transfer
• Upper-Intermediate English proficiency (B2)
  
  

• Databricks
• Anthropic Claude Code
  
  

• 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