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Goatgroup
Senior Manager, Fraud Analytics and Risk
datafull-timeRemote US
SALARY
Not listed
WORK TYPE
remote
JOB TYPE
full-time
INDUSTRY
general
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About the role
Role Overview
We're looking for a sharp, self-driven Senior Manager to join our growing Trust & Safety team. You'll own the full fraud lifecycle — from individual order review to designing AI-enabled detection strategies and presenting risk exposure to executive leadership. This is a forward-looking role: you'll connect the dots across data, drive findings to resolution, and bring new ideas before problems escalate.
You'll work across Product, Engineering, Decision Science, Compliance, CX, and senior leadership — so translating complex findings into clear, actionable narratives is just as important as finding them.
In this role, you will:
- Own the fraud rule lifecycle — designing, testing, deploying, and continuously optimizing detection rules and thresholds to maximize catch rate while minimizing friction.
- Lead AI-enabled fraud use cases end-to-end: use-case sizing, feature ideation, population analysis, and data quality assessment to ensure solutions are analytically sound and value-accretive.
- Conduct periodic performance reviews of fraud models and rules; drive root-cause investigations to proactively surface risk before it scales.
- Serve as a trusted advisor for AI and ML use cases within fraud, ensuring alignment with enterprise AI governance standards, regulatory expectations, and the AI Use Case Registry.
- Evaluate vendor fraud solutions through an analytical lens — assessing effectiveness, overlap, and value relative to cost and risk-reduction objectives.
- Stay current on AI and automation tools and actively explore how they can enhance fraud detection workflows and efficiency.
- Write and maintain intermediate-to-advanced SQL queries to investigate fraud signals, identify connected accounts and orders, and surface emerging patterns.
- Develop and maintain executive dashboards covering fraud review rates, chargeback performance, model effectiveness, and loss trends.
- Translate complex analytical findings into clear, executive-ready narratives — articulating implications for fraud loss, operational efficiency, and customer experience.
- Proactively identify trends and anomalies at both the individual order and systemic level, communicating the full arc of a problem — from discovery to resolution — to any audience.
- Support daily fraud review operations — account verification, order review, escalation handling, SLA adherence, and QA.
- Serve as an internal escalation point for complex cases; assist in coaching the team and continuously improve review processes.
- Partner cross-functionally with Product, Engineering, Compliance, and Legal to align fraud controls with regulatory requirements and product priorities.
- Manage law enforcement requests as needed.
We are looking for:
- 4–6 years in fraud analytics, fraud strategy, or payments risk — ideally within fintech, e-commerce, or a marketplace.
- Demonstrated experience designing and optimizing fraud detection rules or model-driven thresholds.
- Strong SQL proficiency — complex queries from scratch, data troubleshooting, and data storytelling; Snowflake or similar a plus.
- Hands-on experience with order-level fraud review, chargebacks, dispute management, and regulatory compliance.
- Proven ability to build risk reporting and stakeholder dashboards, and present findings confidently to both technical peers and senior leadership.
- Experience with AI-enabled workflows and/or an active interest in applying AI to fraud and risk — including responsible, governance-aligned use.
- Self-starter who synthesizes complex information quickly, drives projects forward without heavy oversight, and connects individual cases to systemic patterns.
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