Model Validation Expert

AI in this role

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.
Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

How we rate this

Model Validation Expert at Bloomberg rates 32 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.