Skills and Competencies - Experience in data science, machine learning, or applied AI, 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 - comfortable reasoning about where these techniques outperform classical methods and where they do not
- Strong programming skills in Python, with practical experience deploying models and services into production
- Practical, hands-on 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
- Exposure to 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: 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 machine learning 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
Education - Degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field is required; a Master's or Ph.D. in a related discipline is preferred, but not required
Responsibilities Lead the design, development, and delivery of innovative AI, machine learning, and generative AI solutions that create meaningful value for clients and advance product capabilities across the Corporate and Governments business.
- Lead the end-to-end design, development, and deployment of machine learning, AI, and generative AI solutions that enhance existing products and enable new client-facing capabilities
- Partner with product, engineering, and business stakeholders across the Corporate and Governments business to translate client needs and market opportunities into well-scoped data science initiatives
- Own model selection, experimentation, and validation end-to-end, ensuring solutions are accurate, scalable, compliant with applicable regulations and legal frameworks, and production-ready
- Identify opportunities for automation and model-based enhancement, applying machine learning and deep learning methods to improve accuracy, efficiency, and overall performance
- Foster best practices in coding, experimentation, machine learning operations, and software engineering excellence
- Drive responsible AI practices across the team, including risk management, model governance, and the ethical use of AI and machine learning techniques
- Communicate technical work clearly and concisely, ensuring insights, limitations, and implications are understood by a broad range of stakeholders, including senior leaders
About the Team Our Data Science, Machine Learning and Engineering team, part of the broader Corporate and Governments Data Team, is responsible for designing, building, and enhancing products through AI, machine learning, and generative AI solutions that deliver innovation and value to clients. By joining the team, you will work at the forefront of applied AI and generative AI, translating advanced techniques into client-facing products, collaborating with a global cross-functional data organization, and helping shape a growing practice focused on the responsible, ethical, and impactful use of artificial intelligence.
For US-based roles only: the anticipated hiring base salary range for this position is $116,500.00 - $169,000.00, 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 is eligible for incentive compensation. Moody's also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.
