Fitt Talent Partners is a specialized recruitment firm working with top health and wellness companies.
We’re filling this role for a client, a leading consumer Health & Wellness Platform — that has existing partnerships with Eight Sleep, WHOOP, Momentous, Peloton, and other top brands.
We enable consumers to pay for eligible health & wellness expenses with HSA/FSA. As we scale, we need a dedicated fraud & risk operator to protect our customers, partners, and the business while keeping approval rates high and friction low.
This is our first fraud hire. You’ll own the day-to-day detection, investigation, and remediation of fraud and abuse across our payment flows and customer/partner lifecycle. You’ll also build the foundations: dashboards, playbooks, controls, and partner/vendor workflows. You’ll work cross-functionally with Product, Engineering, Data, Ops/Support, Finance, and Legal to find root causes and ship fixes that stick.
Real-Time Monitoring & Response
Detect, triage, and respond to fraud attacks (e.g., card testing, account takeover, refund/chargeback abuse, synthetic identity) using internal and external tools
Own incident response for risk events: contain, investigate, document, and drive remediation; participate in on-call/escalation coverage as needed
Investigations & Decisioning
Perform high-judgment investigations and make consistent allow/deny/hold decisions for transactions, accounts, and partner activity
Build decision frameworks and escalation paths that balance fraud loss, customer experience, and regulatory/compliance constraints
Disputes, Inquiries, and Chargebacks (Hands-On)
Own dispute operations end-to-end, including the “minutiae”: monitoring and responding to dispute inquiries/alerts, customer communications, evidence gathering, representment submission, and deadline management
Maintain clean case notes and audit trails; ensure timely, accurate responses that maximize win rate while minimizing customer friction
Analyze dispute reason codes and inquiry drivers; implement prevention tactics (policy/process changes, product nudges, data sharing with Support/Ops) to reduce repeat disputes and friendly fraud
Measurement, Dashboards, and Controls
Define and track core risk metrics (fraud loss, net loss, chargeback rate, approval rate, manual review rate, false positives, backlog health)
Build reporting and propose/implement controls: velocity rules, blocklists/allowlists, step-up verification, 3DS/issuer strategy (where applicable), and policy updates
Cross-Functional & External Partnerships
Work closely with Product/Engineering/Data to translate patterns into tooling and product changes (signals, rules, internal admin tools, case management)
Manage external relationships as needed (processors/acquirers, fraud vendors, card networks/issuers) and drive to underlying fixes, not just band-aids
Minimum Qualifications
3+ years in fraud, risk, trust & safety, investigations, or payments ops in a fintech, payments platform, marketplace, or high-scale consumer product
Strong payments fundamentals: card-not-present risk patterns, dispute/chargeback mechanics (including inquiries), and how controls impact approval rate + customer experience
Strong analytical ability; comfort with SQL, ability to build dashboards, and measure interventions
Demonstrated ability to run ambiguous, 0→1 operating problems: define processes, set metrics, create playbooks, and iterate quickly
Excellent written and verbal communication; calm, precise execution during incidents
High integrity and good judgment handling sensitive data and customer-impacting decisions
Preferred Qualifications
Deep experience owning disputes/chargebacks, including inquiry handling, representment, and win-rate optimization
Familiarity with common fraud tooling and data sources (device/email/phone intelligence, KYC signals, chargeback tools, internal rule engines)
Experience partnering with Engineering/Data Science to build detection signals, internal tooling, or automated controls
Healthcare/benefits/regulated-financial-product experience (nice to have)
Los Angeles / SF / Austin preferred // Remote-available