Location
London

Hours
Full Time

Salary
Negotiable

About the Role
At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities by fostering an inclusive environment where everyone feels welcome to be themselves—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.

As Assistant Director - Data Science, you will lead the design, development, and delivery of innovative AI, machine learning (ML), and generative AI (GenAI) solutions that create meaningful value for clients and advance product capabilities across the Corporate and Governments business. You will own the end-to-end lifecycle of ML and AI solutions, partnering with product, engineering, and business stakeholders to translate client needs and market opportunities into well-scoped data science initiatives.

Your responsibilities will include model selection, experimentation, validation, deployment, and ongoing monitoring to ensure solutions are accurate, scalable, compliant, and production-ready. You will identify opportunities for automation and model-based enhancement, foster best practices in coding, experimentation, ML operations, and software engineering excellence, and drive responsible AI practices including risk management, model governance, and ethical AI use.

You will communicate complex technical work clearly to senior leaders, cross-functional partners, and non-technical stakeholders, helping shape a growing practice focused on the responsible, ethical, and impactful use of artificial intelligence.

Join our Data Science, Machine Learning & Engineering (DSMLE) team, part of the broader Corporate and Governments Data Team, working at the forefront of applied AI and GenAI to deliver innovation and value to clients globally.

Experience
- Experience and/or exposure in data science, machine learning, or applied artificial intelligence, including collaboration with data scientists and engineers
- Hands-on experience building, training, and evaluating machine learning and deep learning models, including modern architectures such as transformers
- Strong programming skills in Python with practical experience deploying ML models and services into production
- Practical experience using AI coding assistants and agentic developer tools such as Claude Code and OpenAI Codex
- Strong working knowledge of large language models (LLMs), including prompting, fine-tuning, retrieval-augmented generation (RAG), and evaluation techniques
- Experience with agentic AI frameworks and libraries in Python, such as AWS Bedrock AgentCore, LangChain/LangGraph, CrewAI, or OpenAI Agents SDK
- Ability to own the full model-development lifecycle including problem framing, data exploration, solution design, estimation, validation, deployment, and monitoring
- Working knowledge of cloud-based data and ML platforms such as AWS, Azure, GCP, and Databricks
- Deep expertise in AI with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency
- Demonstrated leadership in managing AI-related risks, ethical governance, and fostering responsible AI adoption

About you
You are a strategic thinker and effective communicator who can clearly explain complex modeling work to senior leaders and non-technical stakeholders. You lead with curiosity, champion diverse perspectives, and uphold trust through integrity. You are passionate about innovation and responsible AI practices, and you thrive in a collaborative, fast-paced environment focused on delivering impactful AI solutions.

Qualifications
A 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.