Seeking a Ph.D. graduate intern for Quantitative Portfolio Risk Analytics, focusing on developing advanced models to analyze portfolio risk and market structures.
Ideal candidates from cross-disciplinary, research-oriented fields such as physics, math, statistics, engineering, computer science, or biotech are encouraged to apply.
Key tasks include building risk models, analyzing large financial datasets, developing analytical tools using Python and SQL, and collaborating across teams to enhance data infrastructure and model performance.
Qualifications include current Ph.D. enrollment in a quantitative discipline, strong skills in probability, statistics, Python, and data handling; familiarity with finance concepts and advanced methodologies is preferred.
Offers exposure to real-world finance challenges, collaboration with a multidisciplinary team, and potential pathway to full-time roles. Duration: Summer 2026, paid internship with possible extension.