# Senior Quantitative Analytics Specialist – AIM Fraud Modeling at Wells Fargo

Wells Fargo is hiring a Senior Quantitative Analytics Specialist – AIM Fraud Modeling. Level rates it Little AI ●○○○; you can [apply on Wells Fargo](https://jobsbylevel.com/go/b3f864e0-6dd8-4190-8222-7dc5cedd2118?utm_medium=ai-agent).

AI Level 1, AI centrality 13 out of 100. CHARLOTTE, NC.

## Details

- Company: [Wells Fargo](https://jobsbylevel.com/companies/wells-fargo)
- AI level: AI Level 1 (score 13 out of 100)
- Location: CHARLOTTE, NC
- Posted: October 20, 2026
- Apply: https://jobsbylevel.com/go/b3f864e0-6dd8-4190-8222-7dc5cedd2118?utm_medium=ai-agent

## Prepare for this job

The job page lists 5 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/senior-quantitative-analytics-specialist-aim-fraud-modeling-at-wells-fargo-33f602

## Description

Why Wells Fargo Are you looking for more? Find it here. At Wells Fargo, we're more than a financial services leader – we’re a global trailblazer committed to driving innovation, empowering communities, and helping our customers succeed. We believe that a meaningful career is much more than just a job – it’s about finding all of the elements to help you thrive, in one place. Living the Well Life means you’re supported in life, not just work. It means having robust benefits, competitive compensation, and programs designed to help you find work-life balance and well-being. You’ll be rewarded for investing in your community, celebrated for being your authentic self, and empowered to grow. And we’re recognized for it – Wells Fargo once again ranked in the top three – making us the #1 financial services employer – on the 2025 LinkedIn Top Companies list of best workplaces “to grow your career” in the U.S. Join us! About this role: Wells Fargo is seeking a Senior Quantitative Analytics Specialist within the AI Innovation Modeling (AIM) group under COO Data, Analytics & AI . This is a high-impact opportunity for an experienced quantitative professional who is motivated by developing, validating, and advancing machine learning models that detect and prevent fraud. You will work with large-scale transaction and application data to uncover emerging fraud patterns, engineer predictive features, develop and assess sophisticated models, and strengthen model performance from research through production implementation. The role combines hands-on model development with rigorous validation, documentation, governance, and partnership across fraud, technology, model risk, audit, and business teams. This role is ideal for someone who enjoys solving complex analytical problems, challenging model assumptions, translating technical findings for varied audiences, and seeing their work improve customer protection and business outcomes. In this role, you will: Lead the end-to-end development and enhancement of machine learning and statistical models used for real-time fraud risk assessment, transaction or application ranking, and fraud prevention. Analyze millions to billions of records in big data environments to identify predictive fraud signals, evolving attack patterns, and opportunities to reduce fraud losses while supporting a strong customer experience. Build robust Python-based modeling pipelines, including data preparation, sampling, feature engineering, feature selection, model training, testing, and performance evaluation. Apply and assess advanced techniques such as gradient boosting, random forests, isolation forests, support vector machines, neural networks, autoencoders, sequence models, and other fit-for-purpose approaches. Perform independent model validation and effective challenge by evaluating conceptual soundness, data quality, assumptions, methodology, implementation, performance, stability, limitations, and ongoing monitoring results. Design evaluation strategies using appropriate fraud-model measures, threshold analysis, out-of-time testing, back-testing, sensitivity analysis, and benchmarking to confirm models are reliable and fit for purpose. Lead debugging, testing, code review, and performance tuning for machine learning and statistical models developed in Python and distributed computing environments. Document model methodology, validation evidence, assumptions, limitations, controls, and performance outcomes in a clear, reproducible, and governance-ready manner. Present analytical findings and recommendations to technical and non-technical audiences, including fraud leaders, business stakeholders, model validation, model risk, internal audit, governance partners, and regulatory reviewers. Partner across business, technology, data, and risk teams to move analytically sound fraud solutions into production and ensure models continue to address changing fraud threats. Mentor or provide technical leadership to quantitative

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/senior-quantitative-analytics-specialist-aim-fraud-modeling-at-wells-fargo-33f602

Source: https://jobsbylevel.com/jobs/senior-quantitative-analytics-specialist-aim-fraud-modeling-at-wells-fargo-33f602

## Cite this page

Level. https://jobsbylevel.com/jobs/senior-quantitative-analytics-specialist-aim-fraud-modeling-at-wells-fargo-33f602.

Get job alerts: https://jobsbylevel.com/newsletter