Model Validation Expert , NY Posted

Model Validation Expert

Location:

New York

Business Area:
Legal, Compliance, and Risk

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Position Overview

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.

• 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.

• 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.

• 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,…