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Risk Model Validation Jobs (NOW HIRING)

Sitting within the Chief Risk Office as second line of defense, you will play a critical role in executing independent model validation and strengthening the firm's Model and Methodology Risk ...

Lead Model Validation

Chicago, IL · Hybrid

$95K - $163K/yr

Validate a broad range of models used across credit risk, treasury management (ALM), finance, underwriting, and related areas, includes both traditional statistical models and artificial intelligence ...

Work closely within the Risk organization to validate accuracy and performance of all models, whether statistical/AI/ML or non-statistical to identify any issues requiring further investigation, and ...

Lead Model Validation

Chicago, IL · On-site

$95K - $163K/yr

Validate a broad range of models used across credit risk, treasury management (ALM), finance, underwriting, and related areas, includes both traditional statistical models and artificial intelligence ...

Model Risk Management, MRM is responsible for overseeing enterprise-wide model risk management and ... Effective validation helps to ensure that models are sound, identifying potential limitations and ...

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Risk Model Validation information

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$22

$51

$78

How much do risk model validation jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for risk model validation in the United States is $52.00, according to ZipRecruiter salary data. Most workers in this role earn between $39.42 and $63.22 per hour, depending on experience, location, and employer.

What is risk model validation?

Risk model validation is the process of assessing and ensuring that a financial or statistical risk model is accurate, reliable, and appropriate for its intended use. This typically involves reviewing the model's design, data inputs, assumptions, and performance against real-world outcomes. The goal is to identify any weaknesses, limitations, or errors in the model so that organizations can manage risks more effectively and comply with regulatory requirements. Risk model validators often use back-testing, stress testing, and benchmarking against industry standards as part of the validation process.

What are the key skills and qualifications needed to thrive in risk model validation?

To thrive in Risk Model Validation, you need a strong background in quantitative finance, statistics, and risk management, often supported by degrees in mathematics, finance, or related fields. Familiarity with programming languages (such as Python, R, or SAS), statistical modeling tools, and regulatory frameworks like Basel III is essential. Attention to detail, analytical thinking, and effective communication are important soft skills for articulating findings and collaborating with stakeholders. These skills ensure the accuracy and integrity of risk models, which are critical for informed decision-making and regulatory compliance in financial institutions.

What are some typical challenges faced in a risk model validation role, and how can candidates prepare for them?

Professionals in Risk Model Validation often encounter challenges such as staying current with evolving regulatory standards, managing large and complex datasets, and clearly communicating technical findings to non-technical stakeholders. To prepare, candidates should strengthen their understanding of regulatory frameworks (like SR 11-7 or Basel guidelines), develop strong quantitative and programming skills, and practice translating complex model results into actionable business insights. Being proactive in continuous learning and open collaboration with risk, audit, and business teams is also key for success in this dynamic field.

What is the difference between Risk Model Validation vs Credit Risk Analyst?

AspectRisk Model ValidationCredit Risk Analyst
Primary FocusAssessing the accuracy and robustness of risk modelsAnalyzing credit data to evaluate borrower risk
CertificationsFRM, CFA, or similarCFA, Credit Certifications
Work EnvironmentQuantitative, model development teamsCredit departments, lending teams
Industry UsageFinancial institutions, risk management firmsBanks, lending institutions

Risk Model Validation primarily focuses on testing and validating risk models to ensure their accuracy, while Credit Risk Analysts evaluate individual credit data to assess borrower risk. Both roles require quantitative skills and relevant certifications but differ in their specific responsibilities and work environments.

More about Risk Model Validation jobs
Infographic showing various Risk Model Validation job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $108,152 per year, or $52 per hour.

Model Validation Expert

Bloomberg LP

New York, NY • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 days ago


Bloomberg rating

9.4

Company rating: 9.4 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

11th of 245 rated software companies


Job description

Model Validation Expert
Location
New York
Business Area
Legal, Compliance, and Risk
Ref #
10052595
Description & Requirements
Model Validation Expert
(Second Line of Defense)
Position Overview
The energy of a newsroom, the pace of a trading floor, the buzz of a recent tech breakthrough; we work hard, and we work fast - while keeping up the quality and accuracy we're known for. It's what keeps us inventing and reinventing, all the time. Our culture is wide open, just like our spaces. We bring out the best in each other through collaboration. Through our countless volunteer projects, we also help network with the communities around us, too. You can do amazing work here. Work you couldn't do anywhere else. It's up to you to make it happen.
About the Role:
We're looking for a Model Validation Expert to lead independent validation of Bloomberg's ESG Scoring and analytics models. Sitting within the Chief Risk Office as second line of defense, you will play a critical role in executing independent model validation and strengthening the firm's Model and Methodology Risk Management (MRM) program as Bloomberg navigates its obligations under ERR.
This is a senior technical role with a primary focus on ESG Scoring and ESG analytics models. You will assess the conceptual soundness, methodological integrity, implementation accuracy, and performance monitoring practices of Bloomberg's ESG scoring and ratings methodologies. The role may also extend to related quantitative, AI/ML, and data-driven models across the firm.
Operating at the intersection of quantitative analysis, regulatory compliance, and ESG data governance, you will ensure that Bloomberg's ESG Scoring models are fit for purpose, methodologically defensible, and aligned with both internal risk standards and ERR obligations. Your work will enable leadership to understand model limitations, assumptions, and risks - and to demonstrate to regulators and clients that Bloomberg's ESG ratings are produced with rigor, transparency, and appropriate independent oversight.
Key Responsibilities
Lead independent end-to-end validations of Bloomberg's ESG Scoring and analytics models
Assess ESG scoring methodologies for conceptual soundness, data source quality, weighting approaches, aggregation logic, and alignment with stated rating objectives - with specific attention to ERR disclosure and methodology transparency requirements
Evaluate Bloomberg's compliance with ERR model-related obligations, including methodology documentation standards, and public disclosure requirements for ESG rating methodologies
Evaluate backtesting, benchmarking, sensitivity analysis, stress testing, and ongoing performance monitoring frameworks
Review model documentation to ensure transparency, reproducibility, and appropriate articulation of assumptions and limitations
Identify model risks arising from data dependencies, parameter instability, model drift, overfitting, bias, or inappropriate use
Issue clear validation findings, risk ratings, and actionable remediation recommendations
Monitor remediation plans and re-validation activities to ensure sustainable risk reduction
Prepare and present validation conclusions to leadership committees and governance forums
Partner with Engineering, Product, Quants, and Risk Advisors to strengthen model development standards and lifecycle controls while maintaining independence
Contribute to the evolution of the firm's model validation standards, methodologies, and best practices
Stay at the forefront of regulatory developments under ERR, emerging ESG data and analytics standards, and quantitative methods relevant to ESG scoring and model risk management
Required Qualifications
PhD in Mathematics, Statistics, Physics, Financial Engineering, Computer Science, Econometrics, or related quantitative field
10+ years of experience in quantitative modeling, model validation, or model risk management
Deep expertise in pricing, risk, statistical, and/or AI/ML models
Excellent programming skills (Python, C++ required; R, MATLAB, or similar a plus)
Demonstrated ability to independently challenge complex mathematical and machine learning models
Excellent communication skills with ability to translate technical findings into executive insights
Authorized to work in the United States
Preferred Qualifications
Familiarity with the EU ESG Ratings Regulation (ERR) and its model governance, methodology transparency, disclosure requirements, and broader knowledge of model risk frameworks (e.g., SR 11-7, SR 26-2)
Experience engaging with regulators on model risk or ESG rating topics, including interactions with ESMA or national competent authorities under ERR
Relevant professional certifications (e.g., CFA, FRM)
Prior exposure to ESG data, sustainability frameworks (e.g., GRI, SASB, TCFD, ISSB/IFRS S1-S2), or ESG ratings methodology development or review
Core Competencies
Strong intellectual curiosity, commitment to technical excellence, and ability to operate with integrity in a fast-paced environment
Passion for advancing risk governance while enabling innovation in finance and technology
Exceptional analytical rigor and independent judgment
Salary Range = 145,000 - 175,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
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About Bloomberg

Sourced by ZipRecruiter

Bloomberg runs on data. As the Data Management & Analytics team within Engineering, we support our organization's needs around managing data efficiently. The vision of the team is to build solutions that drive data quality, data dictionary, data stewardship, data lineage, reference, and master data management across various data domains (prospect, customer, vendor, material etc.). We partner with business teams across the organization in addressing their data needs and ultimately helping run business operations efficiently and make improved decisions.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1981