Quantitative Associate: AI-Driven Investing & Risk Analytics

Duke Clinical Research Institute; Durham (NC); On-site; USD 125,000 - 140,000; Full time

Benefits offered by this job

Impact on university mission

Exposure to diverse markets

Mentorship and professional growth

Collaborative culture

Job summary

DUMAC invites applications for a Quantitative Associate/Analyst to work across Public, Private, and Direct portfolios, with hands‑on exposure to data science and risk analytics. The role emphasizes cross‑functional collaboration and practical impact through actionable modeling and visualization.

Join a data‑driven team that develops risk models, informs liquidity management, and applies AI/ML to improve investment decisions.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field (Finance, Economics, Statistics, CS, Engineering, or Math).
• Strong proficiency in R or Python for data analysis, modeling, and automation.
• Experience with dashboards and data visualizations using R Shiny, Python Dash, Tableau, or Power BI.
• Familiarity with ML libraries (scikit-learn, TensorFlow, PyTorch) and techniques.
• Experience with SQL querying.

Responsibilities

• Analyze and model portfolio exposures, performance, and risk across asset classes.
• Develop quantitative models to assess manager factor exposures and drivers of return.
• Backtest systematic investment strategies in collaboration with teams.
• Explore and implement AI/ML techniques to enhance decision‑making and workflows.
• Design, build, and maintain dashboards to communicate insights to stakeholders.

Skills

R or Python for data analysis

SQL

Dashboards and data visualizations

Communication skills

ML libraries familiarity

Education

Bachelor’s or Master’s degree in a quantitative field

Tools

R Shiny

Python Dash

Tableau

Power BI

Job description

DUMAC invites applications for a Quantitative Associate/Analyst to work across Public, Private, and Direct portfolios, with hands‑on exposure to data science and risk analytics. The role emphasizes cross‑functional collaboration and practical impact through actionable modeling and visualization.

Join a data‑driven team that develops risk models, informs liquidity management, and applies AI/ML to improve investment decisions.