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Quantitative Model Validation Analyst Jobs (NOW HIRING)

Model Validation Expert Location New York Business Area Legal, Compliance, and Risk Ref # 10052595 ... Operating at the intersection of quantitative analysis, regulatory compliance, and ESG data ...

Model Validation Expert

Manhattan, NY · On-site

$150 - $200/hr

About the Role We're looking for a Model Validation Expert to lead independent validation of ... Operating at the intersection of quantitative analysis, regulatory compliance, and ESG data ...

As a Senior Model Validation Analyst, you will independently evaluate sophisticated scientific, engineering, and financial model components, turning complex data into clear evidence that models are ...

Senior Model Validation Analyst

Boston, MA · On-site

$93K - $116K/yr

As a Senior Model Validation Analyst, you will independently evaluate sophisticated scientific, engineering, and financial model components, turning complex data into clear evidence that models are ...

The candidate will develop, validate, test, document, and implement complex statistical models used ... The candidate will receive direction from their manager and other senior analysts, while also ...

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Quantitative Model Validation Analyst information

See salary details

$56.5K

$133.9K

$240K

How much do quantitative model validation analyst jobs pay per year?

As of Sep 7, 2026, the average yearly pay for quantitative model validation analyst in the United States is $133,877.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $145,500.00 per year, depending on experience, location, and employer.

What is a quantitative model validation analyst?

Quantitative Model Validation Analysts are professionals who assess and validate financial models used by banks and financial institutions. They ensure that these models are accurate, reliable, and comply with regulatory standards. Their work involves testing model assumptions, reviewing model methodologies, and analyzing model outputs to identify potential risks or weaknesses. By providing an independent review, they help organizations maintain the integrity and performance of their risk management and financial forecasting tools.

What are some typical challenges faced by quantitative model validation analysts when assessing complex financial models?

Quantitative Model Validation Analysts often encounter challenges such as interpreting intricate model methodologies, ensuring data integrity, and effectively communicating technical findings to stakeholders who may not have a quantitative background. Additionally, staying current with evolving regulatory requirements and industry standards can be demanding. Collaborating closely with model developers, risk managers, and auditors is crucial to address model limitations and propose actionable improvements, making strong communication and analytical skills essential for success in this role.

What are the key skills and qualifications needed to thrive as a quantitative model validation analyst, and why are they important?

To thrive as a Quantitative Model Validation Analyst, you need a strong background in quantitative finance, statistics, and programming, typically supported by a degree in mathematics, finance, or a related field. Familiarity with statistical software such as Python, R, MATLAB, and model risk management frameworks is essential, and certifications like FRM or CFA are advantageous. Analytical thinking, attention to detail, and effective communication skills set top performers apart by enabling them to explain complex model risks and recommendations clearly. These skills and qualities are vital for ensuring the accuracy, reliability, and regulatory compliance of financial models within an organization.

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

AspectQuantitative Model Validation AnalystQuantitative Risk Analyst
CredentialsTypically requires a degree in finance, mathematics, or statistics; certifications like CFA or FRM are commonSimilar credentials; often holds CFA, FRM, or related certifications
Work EnvironmentFocuses on validating models used in risk management, trading, or credit scoring within financial institutionsAnalyzes and manages financial risk, including market, credit, and operational risks in banking or investment firms
Industry UsageCommonly employed in banking, asset management, and insurance sectorsWidely used in banking, hedge funds, and financial services

The main difference is that Quantitative Model Validation Analysts focus on testing and validating models to ensure accuracy and compliance, while Quantitative Risk Analysts assess and manage overall financial risks. Both roles require strong quantitative skills and often overlap in credentials and work environments, but their core responsibilities differ in scope and focus.

More about Quantitative Model Validation Analyst jobs

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Cities with the most Quantitative Model Validation Analyst job openings:

What states have the most Quantitative Model Validation Analyst jobs?

States with the most job openings for Quantitative Model Validation Analyst jobs include:

What job categories do people searching Quantitative Model Validation Analyst jobs look for?

The top searched job categories for Quantitative Model Validation Analyst jobs are:

Infographic showing various Quantitative Model Validation Analyst job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 82% In-person, 12% Hybrid, and 6% Remote job distribution, with an average salary of $133,877 per year, or $64.4 per hour.

Model Validation Expert

Bloomberg LP

New York, NY • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 25 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 247 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