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Analytics Lead, Deposit Fraud Risk

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Remote from
USA
Salary
USD 164k–245k / yr
Employment
Full Time
Experience
Director
Published
Apply before
2 Nov 2026
Listing views
36
Application actions
2
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AI Summary

The role, at a glance.

Affirm is seeking a senior analytics lead to own fraud performance for depository products, with emphasis on fraud losses, approvals, false positives, customer friction, and portfolio health. The role builds scalable data models, dbt transformation pipelines, dashboards, scorecards, and monitoring frameworks using SQL and Python. It also develops and evaluates fraud rules, policies, thresholds, models, and experiments across identity, account takeover, device, and transaction risk. The successful candidate will partner closely with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk to improve controls and support product launches.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a senior, high-impact risk analytics role requiring 7+ years of experience, strong technical depth, fraud-strategy judgment, and ownership of consequential depository fraud decisions. The role operates during peak fraud activity and requires influencing multiple technical and business teams without direct authority.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$204,500
US market range$160k–$250k
AI insightThe disclosed U.S. yearly base-pay ranges are $164,000–$224,000 for most states and $185,000–$245,000 for CA, WA, NY, NJ, and CT. The combined offer midpoint is $204,500 annually; the estimated U.S. market range for a senior fraud-risk analytics lead is approximately $160,000–$250,000 in base salary, varying by location, financial-services expertise, and scope.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you create a monitoring framework for deposit-fraud performance?

I would first define a governed metric layer covering fraud loss rate, approval and decline rates, false-positive rate, customer friction, operational queues, and cohort-level portfolio health. I would then build validated transformation models and dashboards with segmented views by channel, customer tenure, device, geography, and fraud typology, alongside alert thresholds based on historical variance and materiality. Finally, I would establish an incident-review process that assigns owners, documents root causes, and tracks remediation outcomes.

Describe how you would assess whether a new fraud rule should be launched.

I would define the rule's hypothesis, target population, expected loss reduction, customer impact, operational implications, and guardrail metrics before launch. Where feasible, I would use a randomized holdout or controlled rollout, compare outcomes against a matched baseline, and measure incremental fraud prevented rather than only gross catches. I would recommend scaling only when the net value—including prevented loss, false positives, and operational cost—supports it.

How do you balance fraud-loss prevention with approval rates and customer experience?

I treat fraud strategy as an optimization problem rather than a single loss-minimization exercise. I quantify the marginal value and cost of each decision threshold using expected fraud loss, conversion impact, false-positive cost, manual-review capacity, and customer-friction measures. This enables differentiated strategies that apply stronger controls to high-risk segments while maintaining a low-friction path for trusted customers.

What data-quality practices would you use when building fraud datasets in dbt?

I would define canonical entities and metric definitions, document lineage, and implement tests for uniqueness, freshness, referential integrity, accepted values, and volume anomalies. I would reconcile key outputs to source systems and prior reporting, particularly for transaction, decision, chargeback, and operational timestamps. For production metrics, I would use version-controlled models, peer review, and clear ownership for upstream data contracts.

How would you communicate an emerging fraud trend to non-technical executives?

I would lead with the business impact: what changed, where it is concentrated, the financial and customer risk, and the recommended action. I would use a concise narrative supported by a small number of clear visuals, such as trend lines, segment comparisons, and projected exposure under different actions. I would distinguish confirmed facts from hypotheses and specify the decision, owner, and timeline needed to respond.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

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.

What You’ll Do

This role will take charge of owning fraud performance for depository products, including monitoring fraud losses, approval rates, false positives, customer friction, and other key risk metrics

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.

What We Look For

  • 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 also encourage you to read our Chief Risk Officer’s views on what makes Credit Risk Managers influential and on a Modern Risk Management System.

Base Pay Grade – M

Equity Grade – USA 8

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)

USA base pay range (CA, WA, NY, NJ, CT): $185,000 – $245,000

USA base pay range (all other U.S. states): $164,000 – $224,000

Please note that visa sponsorship is not available for this position.

#LI-Remote

Remote-first with flexibility built in
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.

Benefits designed for you
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.

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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