Model Risk Manager

Mercury

. Perform independent validations and reviews of internally developed and third-party models across credit, fraud, BSA/AML, CECL, finance, liquidity, pricing, and operational risk .

Posted 10/9/2026full-timeRemote • United States, CanadaMid-LevelSenior💰 $128,600 - $160,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in model validation and risk management, with strong analytical capabilities in quantitative risk analytics and familiarity with regulatory expectations. Proficient in using SQL and Python for model evaluation and reporting, while maintaining high standards of documentation and communication.

Highest-signal resume keywords

Model ValidationQuantitative Risk AnalyticsSQL ProficiencyPython ProficiencyModel Risk Management Principles

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Model ValidationQuantitative Risk AnalyticsSQLPythonMachine Learning MethodologiesXGBoostRandom ForestsBSA/AMLCECLCredit Underwriting

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationAttention to DetailSound JudgmentIntellectual Curiosity

Tools & Technologies

Automation ToolsAnalytical ToolsModel Inventory Management

Industry Keywords

Model Risk ManagementRegulatory ExpectationsFinancial ServicesBankingFintech

Tech Stack

Tools & technologies

HaskellPythonSQL

About the role

Key responsibilities & impact

Perform independent validations and reviews of internally developed and third-party models across credit, fraud, BSA/AML, CECL, finance, liquidity, pricing, and operational risk
Evaluate model methodology, assumptions, data quality and lineage, implementation, and performance through outcomes analysis, benchmarking, back-testing, and sensitivity testing
Provide credible and constructive challenges to model developers, owners, and users
Assess model risk and materiality based on inherent risk, purpose, exposure, use, and potential impact
Maintain a complete and accurate model inventory, including 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 fitness for purpose
Evaluate vendor models and third-party analytical products
Document validation conclusions, identify issues, recommend remediation, and track findings through resolution
Support controlled model use when validation cannot be completed before implementation
Develop reporting on model risk, validation coverage, performance concerns, concentrations, dependencies, exceptions, and overdue remediation
Improve Mercury’s Model Risk Management Policy, standards, procedures, and templates
Use automation and analytical tools to improve model inventory management, testing, monitoring, and reporting
Partner with Data and AI Governance teams on boundaries between traditional model risk management and generative AI, agentic AI, and other analytical systems
Support regulatory examinations, Internal Audit reviews, and other assurance activities involving model risk

Requirements

What you’ll need

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
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 areas such as BSA/AML, fraud, financial forecasting, CECL, capital, liquidity, and credit underwriting
Experience with machine learning methodologies such as XGBoost and random forests, scorecards, complex vendor models, and complex spreadsheet-based models
Proficiency with SQL and Python
Strong written and verbal communication skills
Exceptional attention to detail across documentation, code base, testing artifacts and quantitative analysis
Sound judgment and a practical, risk-based mindset
High ownership, intellectual curiosity, and comfort building processes in a fast evolving environment
Master’s degree or PhD is preferred
Experience helping build or materially enhance a model risk management program is preferred
Familiarity with bank regulatory examinations, charter readiness, or implementation of risk programs within a growing financial institution is preferred
Knowledge of Haskell is preferred

Benefits

Comp & perks

Base salary
Equity (stock options/RSUs)
Benefits
Equal Employment Opportunity employer
Reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs