Asst Dir - 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.

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.

Skills And Competencies

• Hands-on experience building, training, and evaluating deep-learning models - not just familiarity with the concepts. You should be comfortable working with modern architectures (e.g., transformers, sequence, and representation-learning models) and reasoning about where they outperform classical approaches and where they don't.
• Ability to explain complex modeling work clearly to senior leaders, cross-functional partners, and non-technical stakeholders, in both writing and speech.
• Strong programming skills in Python or R.
• Depth in one or more deep-learning domains relevant to our work: representation learning for structured financial data, NLP for filings/news/unstructured text, or forecasting for macro and financial time series. (Preferred)
• Exposure to cloud platforms such as AWS, GCP, or Azure. (Preferred)
• Experience developing and deploying models on large, complex, real-world datasets: financial statements, macro time series, text, and other unstructured sources. (Preferred)
• Ability to own the full model-development lifecycle: conceptualization, data exploration, design, estimation, validation, deployment, user training, and monitoring. (Preferred)
• Research output: publications, conference work, or open-source contributions. (Preferred)
  
  

Education

• Ph.D. in Computer Science, Statistics, Applied Mathematics, Economics, Finance, Operations Research, or a related quantitative field; or master’s degree in any of these fields, with 2-3 years of experience in the financial industry.
  
  

Responsibilities

Partner across Moody’s business lines to enhance modeling and analytical frameworks, incorporating state‑of‑the‑art ML and deep‑learning techniques.

• Design and deliver innovative analytical solutions, leveraging deep learning and quantitative methods to address complex financial, economic, and operational problems.
• Identify opportunities for automation and model‑based decision enhancement, applying neural networks, representation learning, and statistical methods to improve accuracy, efficiency, and performance.
• Collaborate with cross‑disciplinary teams to build scalable, cloud‑based analytical platforms grounded in clean, well‑engineered data.
• Apply deep expertise in statistical, machine learning, and deep‑learning methods to develop insights and decision frameworks for internal stakeholders and clients.
• Provide technical leadership, advising business partners on modeling strategy, tradeoffs, and the appropriate role of deep learning in analytical solutions.
• Communicate technical subject matter clearly and concisely, ensuring that insights, limitations, and implications are well understood by diverse audiences.
  
  

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.

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.

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.

For more information on the Securities Trading Program, please refer to the Securities Trading Policy on Moody’s Compliance Expo page

Please note: STP categories are assigned by the hiring teams and are subject to change over the course of an employee’s tenure with Moody’s.