Model Validation Summer Intern

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.

Applications for this position will be accepted from October 13th – October 26th. We encourage interested candidates to apply early to ensure full consideration.

• Exposure to agentic AI - through coursework, academic or personal projects, or a prior internship – for example, building multi-agent workflows involving tool use and orchestration using modern agent frameworks. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use
• Working familiarity with LLM/GenAI fundamentals - prompting strategies, retrieval-augmented generation, function/tool calling, and awareness of common failure modes such as hallucination and prompt injection. Hands‑on project experience is a plus
• An interest in evaluating AI systems (“evals”) - some exposure to accuracy and task‑success testing, grounding and retrieval quality, hallucination detection, and basic benchmarking is preferred
• An interest in AI model risk management, with awareness of the risks and controls specific to Generative AI and agentic AI and their implications for model validation and governance. Exposure through coursework is a plus
• Coursework or personal interest in credit risk, financial products and markets, quantitative modeling, and statistics is valued.
• Proficiency in Python; familiarity with R or SQL is a plus. Comfortable reading and working within an existing codebase
• Academic or project‑based experience spanning AI, machine learning, quantitative analytics, software engineering or related disciplines
• Highly organized, efficient, and detail‑oriented, able to prioritize competing demands, work to tight deadlines, and deliver accurate, high‑quality outputs both independently and collaboratively
• A strong communicator, able to articulate complex ideas fluently and clearly for both technical and non‑technical audiences

• Currently pursuing a Bachelors, Masters, or Doctoral degree in a quantitative or technical field such as computer science, artificial intelligence, machine learning, mathematics, physics or engineering
• Graduation date of December 2027 – June 2029
• Ability to work during program dates:
  June 7th - August 13th 2027

The Quantitative Review Summer Intern role assists in the independent evaluation and challenge of models, scorecards, and agents used in the context of credit rating activities across asset classes, as well as AI model risk management. The successful candidate will contribute to the team’s work on evaluating and governing generative and agentic AI systems, working closely with and learning from experienced validators.

• Support the independent evaluation and challenge of AI‑enabled tools, agents and quantitative models, including hands‑on assessment of inputs, assumptions, conceptual soundness, performance and limitations, with the support of the wider team
• Assist with AI model risk management activities, including the identification, assessment and testing of risks specific to GenAI and agentic AI
• Contribute to validation analyses, including model replication, sensitivity…