Enterprise Portfolio Researcher

Enterprise Portfolio Researcher

We are looking for a motivated Quantitative Risk Modeler with 1- 3 years of experience to join our team. This role focuses on developing and maintaining multi-asset class analytics frameworks to the Firmwide portfolio of teams and senior management decision-making. If you have a passion for quantitative finance, risk modeling, and applied statistics, this is an excellent opportunity to grow your career in a dynamic and collaborative environment.
 

Principal Responsibilities:

• Development of multi-asset class analytics across all MLP strategies, supporting the Office of the CIO across Enterprise-wide initiatives.

• This includes working on the centralized performance evaluation framework at MLP, improvements on VaR and Stress methodologies, as well as implementing centralized back-testing and model performance frameworks.

• Contributions to the development of multi-asset class content generation, as well as centralized visualization tools for the platform used by senior management.

• Ownership in developing a quantitative framework for identifying, measuring, managing, and reporting multi-asset class analytics across the platform

• PM performance measurement and analytics to help inform management decisions.

• Ownership of a multi-asset class stress-testing framework, including insights into key risk drivers to action management decisions.

• Capital utilization and allocation models across portfolio manager teams. Cost of liquidation measurement and management, as well as associated returns relative to constrained resources.

• Post initial model development work, coordinate with relevant Technology departments to ensure changes are deployed into to production.

Qualifications:

• The candidate should have a degree in a quantitative field such as statistics, mathematics, computer science or financial engineering.

• Strong programming skills, prior experience with Python (Polars and/or Pandas). Proficiency in at least a compiled and statically typed language is a plus.

• Knowledge of mathematical and statistical analytics tools: estimation of linear models, dimensionality reduction techniques e.g. Equity Factor Models, Principal Component Analysis, and performance analytics (e.g., Sharpe ratios, drawdowns).

• Sense of responsibility and integrity. Intellectual curiosity and entrepreneurial mindset. Willingness to work and have fun in the process.

• Good presentation and communication skills, experience in either preparing or participating presentation for senior management-style meetings.