Assistant Director - Data Scientist

At Moody's, we unite the brightest minds to turn today's risks into tomorrow's opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are-with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody's is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we're advancing AI to move from insight to action-enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

Skills and Competencies

• Strong theoretical grounding in econometrics, statistics, machine learning, and other quantitative modeling approaches, with demonstrated ability to determine when traditional, machine-learning, or hybrid methods are most appropriate, based on business context, data availability, and interpretability needs
• Experience working with large, real-world datasets: cleaning, merging, exploring, and diagnosing data problems
• Excellent written and verbal communication skills in English, with demonstrated ability to distill complex modeling concepts into clear, audience-appropriate messages for senior leaders, cross-functional partners, and non-technical stakeholders
• Strong programming skills in Python or R, plus working knowledge of SQL
• Fluency with AI productivity tools including coding agents
• Adaptable and curious: comfortable moving between projects and subject areas and learning new domains quickly
• Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use
• Experience in credit risk modeling (e.g., default prediction, early warning, or scoring models) or other financial modeling
• Knowledge of accounting and financial statement analysis
• Experience with large-scale data tools and formats such as Spark, Athena, or Parquet, and general database concepts
• Experience with Git/GitHub in a collaborative development setting
• Exposure to cloud platforms such as AWS, GCP, or Azure
• Familiarity with model documentation and model risk governance standards (e.g., SR 11-7, SR 26-2, etc.)

Education

• Master's degree in Financial Engineering, Data Science, Statistics, Economics, Econometrics, Mathematics, Physics, Finance, Accounting, or a related quantitative field with 2 years of industry experience in quantitative modeling [Required]
• Ph.D. in Financial Engineering, Data Science, Statistics, Economics, Econometrics, Mathematics, Physics, Finance, Accounting, or a related quantitative field [Preferred]
• CPA [Preferred]

Responsibilities

Drive quantitative modeling innovation at Moody's Credit Center of Excellence to enhance credit analytics and predictive modeling capabilities globally.

• Partner across Moody's business lines to enhance modeling and analytical frameworks, incorporating state-of-the-art techniques
• Design and deliver innovative analytical solutions, leveraging quantitative methods to address complex financial, economic, and operational problems
• Build modeling datasets from large, varied sources of financial, market, and firm-level data; assess data quality, handle missing or inconsistent data, and construct sound estimation samples
• Contribute to the ongoing development of established models, including re-estimation, recalibration, performance analysis, and methodology enhancements
• Evaluate when traditional, machine-learning, or hybrid approaches best fit a problem, weighing predictive performance against interpretability, stability, and data limitations
• Write clear model documentation and methodology materials that support internal model governance and client transparency
• Communicate technical subject matter clearly and concisely, ensuring that insights, limitations, and implications are well understood by diverse audiences
• Contribute to projects across the Credit Center of Excellence as priorities evolve, quickly learning existing models, codebases, and subject areas

About the Team

The Credit Center of Excellence (COE) at Moody's is dedicated to developing, enhancing and maintaining our industry-leading credit analytics and predictive modelling capabilities. Our analytics and models are used by institutions worldwide to make credit, risk management, pricing, and investment decisions. We are a global team (spread across all US time zones, GMT, GMT+1) and we work closely with various teams including product management, commercial strategy, and go-to-market leaders to ensure the delivery of high-quality credit risk assessments and solutions. This collaborative approach allows the COE to integrate seamlessly into Moody's structure to support and grow our customers' business operations and enhance their ability to navigate risk.

For US-based roles only: the anticipated hiring base salary range for this position is $132,600.00 - $192,300.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role may be eligible for a completion bonus. Moody's also offers insurance and a discounted employee stock purchase plan for limited duration employees.

For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.

This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody's Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.