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Analytics Lead, Deposit Fraud Risk

Affirm·$164,000 – $245,000

Primary stack

PythonAnalyticsCloud MonitoringSQL

Job description

About the Position

Analytics Lead, Deposit Fraud Risk

Remote US

At Affirm, we exist for the moments that matter-giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.

The Fraud team at Affirm Bank works cross-functionally with Machine Learning, Product, Engineering, Operations to combat fraudulent activities to foster a safe platform.

This role requires abundant cross-functional partnership. This individual will be the representative of the Credit Risk org, leading the charge on refining our Identity Verification and Fraud processes as well as our Application flow. Additionally, this role will work closely with the Product and Engineering teams to improve our Fraud solution.

Come join us in our mission to change consumer finance through better technology, lower costs, and increased transparency while providing the best customer experience.

Responsibilities

Data Pipeline, Analytics & Monitoring

  • Build and maintain scalable data models and transformation pipelines, using tools (such as DBT) to standardize depository product, transaction, customer, fraud, and operational data.
  • Define trusted fraud performance metrics and analytical datasets, including fraud loss rates, approval and decline rates, false-positive rates, customer friction, and operational efficiency.
  • Develop recurring dashboards, scorecards, and monitoring frameworks to provide clear visibility into fraud performance, portfolio health, and emerging risks.
  • Conduct deep-dive analyses to diagnose fraud losses, control gaps, false positives, portfolio shifts, and unexpected performance changes, translating findings into actionable recommendations.

Fraud Strategy Building & Optimization

  • Develop and optimize fraud rules, policies, thresholds, models, and decision strategies that balance loss prevention, customer experience, operational capacity, and product growth.
  • Evaluate new data sources and signals to improve detection of identity risk, account takeover, device risk, transaction risk, and other fraud typologies relevant to depository products.
  • Lead testing and performance measurement of fraud strategy changes, including rule launches, model updates, policy changes, and new product controls, with clear pre- and post-implementation evaluation.
  • Partner cross-functionally with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk to improve fraud strategies, strengthen operational feedback loops, and support new product launches.

Requirements

  • EXPERIENCE: 7+ years’ of Analytics experience
  • PRODUCT KNOWLEDGE: Passion to understand how Affirm product works and a curious mindset to help change and make it more effective
  • TECHNICAL SKILLS: Fluent in SQL and Python
  • PEOPLE SKILLS: A team player with ability to collaborate and influence across many different teams in the organization
  • COMMUNICATION: Ability to communicate findings and recommendations clearly to both technical and non-technical audiences
  • EXECUTION: Able to thrive in a fast-paced environment and be responsive and available during times of peak fraud activity
  • MULTI-TASKING: Strong time management skills and the ability to manage multiple projects and priorities
  • RISK KNOWLEDGE: Working knowledge of the fundamentals of payment processing and an understanding of industry risk trends, including familiarity with fraud strategy development

We Offer

  • Base Pay Grade: M
  • Equity Grade: USA 8
  • Base Pay Range:
    • CA, WA, NY, NJ, CT: $185,000 - $245,000
    • All other U.S. states: $164,000 - $224,000
  • Benefits:
    • Health coverage at no cost
    • Spending stipends for tech setup and health/wellness options
    • Flexible time off and generous holiday calendars
    • Employee stock purchase plan (ESPP)

About the Company

Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.

Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:

  • Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
  • Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
  • Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
  • Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.

We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.

For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.

By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

© Affirm. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.

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Affirm

Financial Services

About the Company Affirm’s mission is to deliver honest financial products that improve lives. The company aims to build a new kind of payment network based on trust, transparency, and prioritizing people. This approach empowers millions of consumers to spend and save responsibly. Products, Services & Tech Stack Core Solutions: Financial products designed to improve consumer lives through responsible spending and saving. Project Scope & Target Clients Client Base: The specific target verticals or client types served are not mentioned in the provided text. Engineering Scale: The scope and complexity of engineering projects are not mentioned in the provided text.

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