Fraud Analytics Lead — Remote & Cross-Functional Risk

Affirm, Inc.; San Diego (CA); Remote; USD 185,000 - 245,000; Full time

Benefits offered by this job

Health coverage at no cost

Monthly tech stipends

Flexible time off

Employee stock purchase plan

Job summary

Affirm, Inc. is seeking a senior data/analytics professional to own fraud performance for depository products. You will monitor losses, approve/decline rates, false positives, and customer friction while guiding analytics improvements and risk strategies.

You will build data models and dashboards using DBT, define metrics, and collaborate with Product, Engineering, ML, and Risk teams to refine identity verification and fraud processes across the application flow.

Qualifications

• 7+ years of Analytics experience.
• Fluent in SQL and Python.
• Strong cross-functional collaboration with Product, ML, Data Eng, and Risk teams.
• Ability to communicate findings clearly to technical and non-technical audiences.

Responsibilities

• Own fraud performance for depository products, monitoring losses, approvals, false positives, and customer friction.
• Build and maintain scalable data models and transformation pipelines (DBT).
• Define fraud performance metrics and analytical datasets; create dashboards and monitoring frameworks.
• Lead testing and evaluation of fraud strategy changes with pre- and post-implementation analysis.
• Partner with Product, Engineering, ML, Data Eng, Fraud Ops, and Risk to improve fraud strategies and product launches.

Skills

SQL

Python

Cross-functional collaboration

Data storytelling

Analytical reasoning

Tools

DBT

Job description

Affirm, Inc. is seeking a senior data/analytics professional to own fraud performance for depository products. You will monitor losses, approve/decline rates, false positives, and customer friction while guiding analytics improvements and risk strategies.

You will build data models and dashboards using DBT, define metrics, and collaborate with Product, Engineering, ML, and Risk teams to refine identity verification and fraud processes across the application flow.