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
- Working knowledge of R and Python with proficiency in at least one. Working knowledge of SQL and different frameworks
- Ability to comfortably work with different data structures and to identify the right data structures for the problem at hand
- Comfort with different types of data at rest- csv, binaries, json, parquets, SQL etc
- Basic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiency. Interest in exploring AI systems and a willingness to develop awareness of responsible AI practices, including risk management and ethical use
Nice to have
- Theoretical knowledge of data encoding, compression, serialization, transfer etc.
- Theoretical knowledge of threading, multiprocessing, IPC, CPU architecture, HPC computing, vectorization
- Demonstrate comfort with Unix based operating systems and shell scripting
- Theoretical knowledge of computer vision and machine learning algorithms and working knowledge of at least one library each
Education
- Graduation date of December 2026 - June 2027
- Ability to work during program dates: June 1st - August 7th 2026
- Preferred: Masters, Phd
Responsibilties
- Prototyping of highly performant data flows across model lifecycle
- Using state of the art Learning and Computer Vision techniques to identify anomalies in data sets using pre-defined heuristics
