Senior Manager, Fraud Analytics and Risk

GOAT Group

1d•$104,480 - $153,600

About The Position

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.

Requirements

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.
Comfortable in a fast-paced environment where priorities shift as the threat landscape evolves.

Responsibilities

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.