Director of Fraud Risk Management

Flex

. Own end-to-end fraud risk management for Flex’s credit card and DDA portfolio across consumer and small business segments .

Posted 11/3/2026full-timeRemote • United StatesLead💰 $150,000 - $250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive expertise in fraud risk management, including detection and loss management across consumer and small business products. Proficient in analyzing fraud patterns, building detection frameworks, and communicating complex fraud dynamics to senior leadership.

Highest-signal resume keywords

Fraud Risk ManagementFraud Detection FrameworksSQL ProficiencyPython ProficiencyFraud Typology Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Fraud Risk ManagementFraud Detection LogicCohort AnalysisLoss AttributionDevice FingerprintingIP IntelligenceBehavioral BiometricsML-Based Anomaly DetectionDDA Fraud VectorsQuantitative Analysis

Soft Skills

Communication SkillsAnalytical ThinkingLeadership

Industry Keywords

KYCKYBSAR FilingReg EFCRABSA/AMLCredit Card FraudSynthetic Identity FraudFinancial CrimesRisk Management

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Own end-to-end fraud risk management for Flex’s credit card and DDA portfolio across consumer and small business segments
Analyze acquisition and onboarding fraud patterns, identity signals, document authenticity, synthetic identity indicators, and approval anomalies
Monitor KYC/KYB verification performance and identify friction or control gaps
Monitor first-party fraud, third-party fraud, synthetic identity fraud, DDA-specific fraud vectors, and authorization/transaction patterns
Own analytical views of disputes, chargebacks, friendly fraud, recovery rates, and loss emergence timing
Build and maintain fraud detection frameworks for emerging attack patterns
Synthesize device, IP, identity, bureau, transaction, and behavioral data to identify coordinated fraud rings and correlated anomalies
Lead periodic fraud risk reviews and present exposure implications to risk committees and senior leadership
Develop fraud segmentation to improve detection tuning, policy intervention, and loss reserve calibration
Partner with credit, legal and compliance, financial crimes, operations, and product teams
Contribute to fraud-loss scenario analysis and stress testing
Serve as the internal subject-matter expert for fraud analytics, detection standards, taxonomy, and measurement frameworks
Report to the Chief Risk Officer as a member of the Risk Management Leadership Team

Requirements

What you’ll need

7–15 years of hands-on fraud risk management experience with direct ownership of detection and loss management across consumer and small business products
Experience spanning both a bank or regulated card program and a fintech strongly preferred
Deep subject matter expertise across first-party, third-party, and synthetic identity fraud typologies
Ability to distinguish fraud typologies analytically across credit card and DDA contexts
Expertise with device fingerprinting, IP intelligence, identity graph analysis, behavioral biometrics, velocity rules, and ML-based anomaly detection
Understanding of DDA fraud vectors, including ACH origination and return abuse, check fraud, Reg E dispute dynamics, and payment fraud/account takeover intersections
Proficiency in SQL and Python or R
Ability to build detection logic, cohort analysis, and loss attribution from raw data
Familiarity with SAR filing thresholds, Reg E obligations, FCRA considerations for adverse action, and BSA/AML red flags
Senior-level perspective on emerging attack vectors and detection assumptions
Ability to model bad-actor exploitation of products, policies, and verification weaknesses
High quantitative aptitude and ability to identify and escalate loss or dispute pattern shifts
Ability to communicate complex fraud dynamics to risk committees, product teams, and senior leadership

Benefits

Comp & perks

Equity in the company in addition to base compensation