Fraud Analytics Manager

Role overview Build the analytics capabilities that help fraud, credit risk, and operations teams make faster, better-informed decisions. This hands-on individual contributor role combines data analysis with automation, shared tooling, and reporting, while helping shape a new function.

Responsibilities - Find and automate repetitive analytics work across fraud and risk, delivering tools that reduce manual effort. - Develop a shared framework for testing fraud rules across account takeover, first-party fraud, identity theft, and credit risk. - Consolidate reporting pipelines and maintain reliable dashboards and data products. - Create consistent risk labels and account for how changes in one area affect others. - Apply AI and language-model tools to analytical workflows, and measure impact through hours saved. - Work with fraud, credit, and risk partners to prioritize improvements and evolve the function’s scope.

Requirements - Strong working proficiency in SQL and Python. - Ability to investigate complex, untidy data and turn findings into practical decisions. - Experience with business intelligence tools, such as Sigma, Tableau, or similar. - Familiarity with Git and collaborative development workflows. - Clear communication, initiative, and a track record of delivering useful solutions. - Approximately 3–6 years of relevant analytics experience; demonstrated skills are the priority.

Nice to have - Experience with language models or prompt design, fintech or startup environments, fraud or credit analytics, or building an analytics function from the ground up.

Benefits and work setup Compensation includes equity. Benefits include flexible paid time off, health coverage for employees and dependents, access to primary care and flexible spending accounts, and paid parental leave (20 weeks for primary caregivers and 8 weeks for other new parents). Work computers are provided, with a choice of configuration.