Imprint Fraud Analytics Manager at Imprint owns the analytics function supporting fraud, credit risk, and operations. The role focuses on building automation, tooling, and reporting infrastructure to reduce manual work and drive smarter decisions.
Responsibilities
This role is net new — it is not a backfill. It is being created to solve problems that are not currently owned well enough and to establish a new type of analytics function at Imprint.
What Success Looks Like in the First 90 Days
Automated or tooled at least 3 manual reports or tasks, delivering complete working solutions for the team
Consolidated overlapping Claude/LLM skills into a more streamlined, shared framework
Built an initial backtesting framework for fraud rules, creating a shared process across ATO, first-party fraud, IDT, and credit risk
Established hours saved per week as the primary KPI for the role, with dashboards and reporting to track it
Earned trust as a doer who takes action, moves fast, and builds things that last
Own end-to-end automation and tooling for manual and redundant analytics tasks across fraud and risk
Build and maintain a consolidated backtesting framework for fraud rules, shared across ATO, first-party fraud, IDT, and credit risk
Consolidate fragmented reporting pipelines and deliver clean, reliable reporting infrastructure
Develop and maintain a consolidated risk label framework so changes in one area account for downstream effects in others
Deploy LLM and AI tooling to streamline analytical workflows
Qualification
Experience with GitClearBias toward action — takes initiativeExposure to fraud
Required
Strong proficiency in SQL and Python — these are non-negotiable
Demonstrated analytical ability and comfort diving into messy, complex data
Experience with BI tooling (Sigma preferred; Tableau or similar accepted)
Experience with Git
Clear, effective communicator who can translate analytical findings into decisions
Bias toward action — takes initiative, ships solutions, and doesn't wait for perfect conditions
Roughly 3–6 years of relevant analytics experience, though skill set matters more than tenure
Preferred
Experience with LLMs and prompt engineering
Background in fintech or a high-growth tech startup
Exposure to fraud, credit risk, or financial domain analytics
Experience building or scaling analytics functions from scratch
