Remote Analytics Lead for Deposit Fraud Risk

Affirm, Inc.; Northern (KY); Hybrid; USD 164,000 - 245,000; Full time

Benefits offered by this job

100% medical coverage for employee and

Monthly tech stipends

Flexible time off

Employee stock purchase plan

Job summary

Affir Bank seeks a senior analytics leader to own fraud performance for depository products, overseeing losses, approvals, false positives, and customer friction. You will build scalable data models, dashboards, and risk assessments in collaboration with Product, Engineering, ML, and Risk teams.

Role requires 7+ years in analytics, strong SQL/Python skills, and the ability to translate complex findings into actionable guidance for cross-functional partners in a fast-paced, remote-first

Qualifications

• 7+ years of analytics experience in a fraud/rraud risk environment.
• Strong SQL and Python fluency.
• Experience partnering with product, engineering, ML, and risk teams.

Responsibilities

• Own fraud performance for depository products, monitor losses, approvals, false positives, and customer friction.
• Develop scalable data models and transformations for fraud and risk data (DBT).
• Define fraud performance metrics and analytics datasets.
• Build dashboards and monitoring for fraud portfolio health and risks.
• Lead testing and evaluation of fraud strategy changes with pre/post analyses.
• Partner across Product, Engineering, ML, Data Engineering, Fraud Operations and Risk to improve fraud strategies.

Skills

Analytics experience

SQL

Python

Cross-functional collaboration

Communication

Fraud domain knowledge

Tools

DBT

Job description

Affir Bank seeks a senior analytics leader to own fraud performance for depository products, overseeing losses, approvals, false positives, and customer friction. You will build scalable data models, dashboards, and risk assessments in collaboration with Product, Engineering, ML, and Risk teams.

Role requires 7+ years in analytics, strong SQL/Python skills, and the ability to translate complex findings into actionable guidance for cross-functional partners in a fast-paced, remote-first