Fraud Detection Engineer Job Description Template

The fraud detection engineer builds the systems that identify and stop fraudulent activity, balancing losses from fraud against the cost of blocking legitimate customers. The role is adversarial, since attackers adapt to whatever is deployed, and it requires both engineering and an analytical understanding of the trade off between false positives and missed fraud.

Typical Duties and Responsibilities

• Build real time fraud detection and scoring systems
• Develop rules and machine learning models for fraud identification
• Engineer features from transaction, device and behavioral data
• Tune thresholds balancing fraud loss against customer friction
• Monitor fraud patterns and adapt detection as attacks change
• Build case management tooling for fraud analysts
• Analyze false positives and their customer impact
• Implement device fingerprinting and behavioral signals
• Report fraud metrics and losses to the business
• Work with analysts and investigators on emerging patterns

Education

• Bachelor’s degree in computer science, statistics or a related field

Required Skills and Experience

• 3+ years building fraud detection or risk systems
• Strong engineering skills for low latency decisioning
• Experience with rules engines and machine learning models
• Understanding of the precision and recall trade off in a commercial context
• Ability to work with heavily imbalanced data
• Experience monitoring and adapting to adversarial change
• Analytical rigour about measuring fraud outcomes
• Collaboration with investigation and operations teams

Preferred Qualifications

• Experience with payment fraud or account takeover specifically
• Familiarity with device fingerprinting techniques