Greenhouse ·
full-timeModel Risk Manager
Mercury · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
Mercury is a financial technology company providing banking services for startups and small businesses. The Model Risk Manager will play a critical role in establishing and maintaining a robust, risk-based model risk management program as the company scales toward becoming a regulated bank. This is a hands-on position that requires a blend of technical expertise and regulatory awareness. Daily responsibilities include conducting independent validations of internal and third-party models used in credit underwriting, fraud prevention, BSA/AML, finance, and liquidity. You will evaluate model methodologies, challenge assumptions, and ensure data quality through rigorous testing such as back-testing and sensitivity analysis. Beyond validation, the role involves maintaining a comprehensive model inventory, monitoring performance, and providing constructive feedback to engineering and product teams. This position is well-suited for a professional with at least five years of experience in model validation, quantitative risk analytics, or financial consulting. The ideal candidate can navigate complex regulatory expectations while maintaining a practical, collaborative approach to risk management within a fast-paced fintech environment.
About the role: Mercury is looking for a Model Risk Manager to help build and operate a practical, risk-based Model Risk Management program as we continue to scale and prepare for life as a regulated bank. Models support an increasingly broad range of decisions across Mercury, including credit underwriting, portfolio management, fraud prevention, BSA/AML, CECL, finance, liquidity, pricing, and operational processes. This role will provide independent review and effective challenge throughout the model lifecycle while helping Mercury apply governance proportionate to the actual risk of each model. This is a hands-on role for someone who can move comfortably between technical analysis, regulatory expectations, and business context. You will conduct model validations, challenge assumptions and limitations, improve our model inventory and monitoring practices, and work closely with teams across Risk Ops, Data, Engineering, Product, Finance, Compliance, and Internal Audit. Showing up as a true collaborator, advisor and partner to the business will be key as we continue to build out this function and work towards our collective goals at Mercury. You should be comfortable operating in a fast-moving environment where the objective is not governance for its own sake, but helping Mercury use models safely, responsibly, and effectively. What you’ll do: Perform independent validations and reviews of internally developed and third-party models across areas such as credit, fraud, BSA/AML, CECL, finance, liquidity, pricing, and operational risk. Evaluate each model’s methodology, assumptions, data quality and lineage, implementation, and performance through reviews and testings such as outcomes analysis, benchmarking, back-testing, and sensitivity testing scaled to its risk and materiality. Provide credible and constructive challenges to model developers, owners, and users while maintaining effective working relationships with 1LOD. Assess model risk and materiality based on a model’s inherent risk, purpose, exposure, use, and potential impact. Help maintain a complete and accurate model inventory, including model ownership, risk rating, dependencies, limitations, validation status, monitoring requirements, and open issues. Review ongoing monitoring plans and results, including performance thresholds, overrides, data drift, model changes, and conditions that could make a model no longer fit for purpose. Evaluate vendor models and other third-party analytical products, including available documentation, transparency, performance, limitations, customization, and Mercury’s ability to monitor and control their use. Document validation conclusions clearly, identify issues, recommend proportionate remediation, and track findings through resolution. Support controlled model use when validation cannot be completed before implementation by helping establish appropriate limitations, compensating controls, monitoring, and approvals. Develop clear reporting on model risk, validation coverage, performance concerns, concentrations, dependencies, exceptions, and overdue remediation for management and governance committees. Help improve Mercury’s Model Risk Management Policy, standards, procedures, and templates. Use automation and analytical tools to make model inventory management, testing, monitoring, and reporting more efficient. Partner with Mercury’s Data and AI Governance teams to establish clear boundaries and handoffs between traditional model risk management and the governance of generative AI, agentic AI, and other analytical systems outside the formal model definition. Support regulatory examinations, Internal Audit reviews, and other assurance activities involving model risk. What we’re looking for: 5+ years of relevant experience in model validation, model development, quantitative risk analytics, or a related discipline within banking, fintech, financial services, or consulting. Bachelor’s degree in Statistics, Mathematics, Physics, Computer Science, Engineering, Financial Engineering or a related field. Master’s degree or PhD is preferred. Strong knowledge of model risk management principles and current regulatory expectations, including the revised interagency guidance reflected in SR 26-2. Intensive experience validating or developing models in one or more areas such as BSA/AML, fraud, financial forecasting, CECL, capital, liquidity, and credit underwriting, using one or more methodologies such as machine learning (e.g., XGBoost, random forests), scorecards, complex vendor models (e.g., Alloy, Firco), and complex spreadsheet-based models. Proficiency with SQL and Python (from a data analytics lens); comfortable building understanding of models independently of their developers through collecting evidence and data analytics. Strong written and verbal communication skills; you can explain model risk to a data scientist and to a regulator, or translate your findings and recommendations to guidance for the 1LOD product/busi
| Role | Model Risk Manager |
|---|---|
| Company | Mercury |
| Location | San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States |
| Type | full-time |
| Compensation | Not disclosed |
| Posted | 2026-10-09 |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4Model Risk Manager at Mercury: frequently asked questions
- What is the salary for this role?
- Mercury has not stated compensation in the listing. Check the original posting or ask during the application process.
- Is the Model Risk Manager position remote, hybrid or onsite?
- The listing marks this role as remote, with San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States as the location.
- What is the application deadline?
- Mercury has not listed a fixed deadline, so apply early in case the opening is filled.
- How do I apply for the Model Risk Manager role?
- Use the Apply button on this page. It opens the original listing on job-boards.greenhouse.io, where you submit your application with the company.
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