Quantitative Researcher - Model Scaling
MSCI · San Francisco
The Factors Research Platform and Governance team is responsible for building and modernizing the infrastructure, tooling, and frameworks that power MSCI's quantitative risk and factor model research. The team develops the systems and environments that enable researchers to iterate quickly, maintain model governance, and deliver production-quality outputs at scale.
- Designing and building modern research infrastructure that integrates AI to accelerate model development, validation, and reporting workflows
- Developing tools and frameworks that allow researchers to move from high-level specifications to production-ready implementations with minimal manual overhead
- Building and maintaining automated validation, testing, and governance pipelines for quantitative models
- Writing production-level code to support platform development and model delivery
- Supporting existing factor and risk models while evolving the platform to enable faster research iteration
- Collaborating cross-functionally with research, engineering, and data teams
- Presenting complex systems and methods to a broad range of audiences
- M.S. or Ph.D. in Finance, Statistics, Computer Science, Engineering, or other quantitative discipline
- Strong software engineering skills, particularly in Python
- Hands-on experience with modern AI-assisted development tools and workflows, with a demonstrated ability to stay current with rapidly evolving AI capabilities and incorporate them into day-to-day work
- Experience building systems and tooling that leverage AI/LLMs to augment technical workflows
- Data analysis and experience with large-scale data infrastructure
- Econometrics and applied statistics
- Ability to work independently and drive projects from design through delivery
- Knowledge of finance or risk modeling is preferred but not required