Assistant Director -Data Science (Machine Learning Engineering)

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

• Experience and/or exposure in data science, machine learning, or applied artificial intelligence, including experience working on projects or collaborating with data scientists and engineers
• Hands-on experience building, training, and evaluating machine learning and deep learning models, including modern architectures such as transformers, with the ability to assess where advanced approaches outperform classical methods and where they do not
• Strong programming skills in Python, with practical experience deploying machine learning models and services into production environments
• Practical experience using AI coding assistants and agentic developer tools such as Claude Code and OpenAI Codex to accelerate development, testing, and code review, with familiarity across the software development lifecycle and machine learning operations practices
• Strong working knowledge of large language models (LLMs), including prompting, fine-tuning, retrieval-augmented generation (RAG), and evaluation techniques, and the ability to apply them to real product challenges
• Experience with agentic AI frameworks and libraries in Python, such as AWS Bedrock AgentCore, LangChain/LangGraph, CrewAI, or the OpenAI Agents SDK, with an understanding of agent design patterns including tool use, orchestration, memory, and multi-agent workflows
• Ability to own the full model-development lifecycle, including problem framing, data exploration, solution design, estimation, validation, deployment, and ongoing monitoring
• Ability to explain, present, and demonstrate complex modeling work clearly to senior leaders, cross-functional partners, and non-technical stakeholders
• Working knowledge of cloud-based data and machine learning platforms such as AWS, Azure, GCP, and Databricks, as well as the broader ecosystem used to build and deploy AI and ML products
• Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization.