CME Group aims to modernize its core analytics and develop new AI-driven, mathematically rigorous models by leveraging its vast financial datasets and strategic partnership with Google Cloud Platform (GCP). The goal is to build next-generation analytics, financial mathematical models, and AI systems to support global financial institutions.
Requirements
- PhD candidate in mathematics, statistics, physics, engineering, computer science, quantitative finance, econometrics, or a related field
- Strong foundation in financial mathematics (stochastic calculus, derivatives modeling, numerical methods, or equivalent)
- Proficiency in Python and scientific computing libraries
- Experience with GCP: BigQuery, Vertex AI, Dataflow, C++
- Experience with ML, embeddings, or agent-based systems
- Background in market microstructure, derivatives, or high-frequency data
- Prior publications, technical reports, or model documentation
Responsibilities
- Review and suggest improvements to analytical models using modern numerical and statistical methods
- Document and validate models in alignment with governance and regulatory standards
- Work with technology to prepare models for deployment using GCP infrastructure
- Help to document and at times direct conversion of legacy codebases into robust, maintainable analytics libraries
- Ensure mathematical transparency, reproducibility, and version control
- Build analytical pipelines using Python + GCP tooling
- Develop visualizations and explainers for internal and client use
Other
- 20 hours/week commitment
- 1–2 days onsite in the Chicago office
- 12-month internship
- Flexible to accommodate academic commitments
- Ability to communicate complex concepts clearly in writing
