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Asst Dir-Data Scientist

LinkedIn Moody's Corporation New York, NY
Not Applicable Posted April 5, 2026 Job link
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Requirements
  • Strong theoretical grounding in econometrics, statistics, and quantitative modeling, with demonstrated ability to determine when deep learning, traditional approaches, or hybrid methods are most appropriate, based on business context, data availability and interpretability needs
  • 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
  • Excellent written and verbal communication skills in English
  • Exposure to cloud platforms such as AWS, GCP, or Azure is desired
  • Experience developing and deploying deep learning models on large, complex datasets (financial statements, macro time series, text, unstructured data) is desired
  • Demonstrated commitment to transparent, well‐structured model documentation and adherence to governance standards
  • Ability to manage the entire model‐development lifecycle—from conceptualization through data exploration, model design, estimation, validation, deployment, user training, and monitoring
  • Partner across Moody’s business lines to enhance modeling and analytical frameworks, incorporating state‐of‐the‐art ML and deep‐learning techniques
Preferred Skills
  • Expertise in machine learning and deep learning, including hands‐on experience with deep-learning architectures, such as transformers and other state-of-the-art frameworks is preferred
  • Exposure to cloud platforms such as AWS, GCP, or Azure is desired
  • Experience with production machine learning systems is preferred
  • Experience developing and deploying deep learning models on large, complex datasets (financial statements, macro time series, text, unstructured data) is desired
  • Demonstrated commitment to transparent, well‐structured model documentation and adherence to governance standards
Education
  • (Not required) – Education
  • (Not required) – Ph.D. in Economics, Finance, Computer Science, Statistics, Applied Mathematics, Operations Research, or a related quantitative field; or a Master’s degree in any of these fields, with 2-3 years of experience in the financial industry