Quantitative Analyst Intern

Each Intern will have a hands-on opportunity to apply classroom knowledge within a real world, large-scale institutional investment organization. Selected interns will contribute to quantitative research, data engineering, machine learning, and artificial intelligence initiatives that support the Investment Division's quantitative research and investment processes. In addition, the interns will assist in establishing and maintaining automated data pipelines and robust data quality controls to ensure the accuracy, timeliness, and integrity of research and production environments, building and maintaining comprehensive feature libraries across macroeconomic, cross-asset, equity, and risk domains to facilitate systematic research and portfolio management, assist in conducting quantitative alpha research utilizing advanced statistical, machine learning, and modern AI techniques to generate and enhance predictive signals and investment insights, and other projects driven by the Investment Division priorities and needs.

As an Intern, you will assist in the following:

• Build and continuously enhance data, analytics, and ML/AI infrastructure to support quantitative research, signal generation, portfolio construction, and investment decision-making.
• Implement scalable tools and workflows that improve research efficiency, reproducibility, and operational robustness across the investment process.
• Partner with investment, technology, and operations teams to translate research requirements into production-ready capabilities and infrastructure.
• Design, develop, and maintain automated data ingestion and processing pipelines to ensure timely and reliable access to investment data.
• Design, develop and maintain data quality control processes to ensure the accuracy, timeliness and integrity of research and production environments.
• Stay abreast of emerging developments in machine learning, artificial intelligence, and quantitative methodologies, and evaluate their applicability to investment research and portfolio management.
• Develop and apply advanced statistical, machine learning, and AI techniques to macroeconomic, cross-asset, equity, and risk datasets to identify predictive relationships and generate alpha signals.
• Research and model macroeconomic trends, market regimes, asset class returns, and risk dynamics to enhance forecasting and support investment decision-making.
• Assist in development  and enhancement  systematic forecasting frameworks for economic conditions, market environments, and asset price movements across global markets.
• Evaluate model performance and continuously refine methodologies to improve predictive accuracy, robustness, and risk-adjusted investment outcomes.
• Translate research findings into actionable insights that support portfolio construction, risk management, and dynamic asset allocation decisions
• Other Projects, as assigned.

Dates of the Internship

The start dates of the internship may be flexible. This is part-time employment. The internship will run about a year from the hiring. This internship will follow a hybrid model: a combination of in-person and virtual presence will be required.