Analytics Lead, Deposit Fraud Risk

Affirm

Confirmed live today High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$185,000–$245,000 / yr
Posted
28 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $187k
This role $215k
$135k $257k
below market most similar roles pay here above market

This role pays more than 72% of similar roles. Most pay $153,575–$220,225 — the blue band above. At the midpoint, this role pays about $215k versus about $187k for comparable roles.

Based on 240 similar postings.

Employer

About Affirm

Affirm is a buy-now, pay-later (BNPL) financial technology company that offers point-of-sale installment loans to consumers, allowing them to split purchases into fixed monthly payments with transparent terms. Industry: Financial Technology & Consumer Lending

Affirm currently has 64 open roles on FindRole.

Listed pay typically runs $195,000–$255,000 across 60 roles with salary data.

Most-posted roles

View all roles at Affirm

At a glance

TL;DR · Analytics Lead, Deposit Fraud Risk

Analytics Lead, Deposit Fraud Risk joins the Fraud team to manage fraud performance for depository products. This role involves owning key risk metrics, including fraud losses, approval rates, and customer friction. You will build and maintain scalable data models and transformation pipelines using DBT to standardize transaction and customer data. Responsibilities include developing recurring dashboards, conducting deep-dive analyses to diagnose control gaps, and optimizing fraud rules and policies. You will evaluate new data signals to improve detection of identity risk, account takeover, and transaction risk. The position requires fluency in SQL and Python to support cross-functional partnerships with Machine Learning, Product, and Engineering teams. You will solve technical problems related to payment processing and fraud strategy development to balance loss prevention with product growth.

What you'll do

  • Own fraud performance for depository products by monitoring losses, approval rates, false positives, and customer friction.
  • Build and maintain scalable data models and transformation pipelines using tools like DBT.
  • Define and monitor trusted fraud performance metrics, dashboards, and scorecards for portfolio health.
  • Conduct deep-dive analyses to diagnose fraud losses, control gaps, and unexpected performance changes.
  • Develop and optimize fraud rules, policies, thresholds, and decision strategies to balance loss prevention and growth.
  • Evaluate new data sources and signals to improve detection of identity risk and transaction risk.
  • Lead testing and performance measurement for fraud strategy changes, including rule launches and model updates.

What we're looking for

  • 7+ years of Analytics experience.
  • Fluency in SQL and Python.
  • Working knowledge of payment processing fundamentals and industry risk trends.
  • Experience with fraud strategy development and fraud performance metrics.
  • Ability to build and maintain scalable data models and transformation pipelines using tools like DBT.
  • Ability to communicate findings clearly to both technical and non-technical audiences.
  • Ability to manage multiple projects and priorities in a fast-paced environment.
  • Ability to collaborate and influence across different teams in the organization.

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