Quantitative Investment Strategist – Portfolio Design & Risk

Referment; New York (NY); On-site; USD 110,000 - 180,000; Full time

Job summary

Referment is seeking a technically oriented strategist to join a portfolio strategy team that develops active equity and multi-asset investment products for institutional clients. You will combine quantitative research, portfolio design, risk analysis, and client communication to help refine investment products and strategies.

You will work closely with portfolio strategy and investment colleagues to explore enhancements, implement robust models, and present findings to both quantitative and

Qualifications

• Bachelor’s degree in a quantitative, scientific, engineering, finance, or economics discipline.
• Basic Python or similar programming skills and interest in clean, testable code.
• Systematic approach to numerical problems and interest in financial markets.
• Strong technical writing and presentation skills.
• Knowledge of numerical and statistical methods is advantageous.

Responsibilities

• Contribute quantitative analysis and portfolio design to investment-product development.
• Research and implement strategy enhancements for portfolio construction and risk modelling.
• Analyse portfolios to identify weaknesses, concentrations, opportunities.
• Produce rigorous technical work and explain findings to stakeholders.
• Support investor discussions and prepare materials on portfolio construction and performance.

Skills

Python basics

Numerical methods

Technical writing

Presentation skills

Finance knowledge

Education

Bachelor's degree in quantitative field

Tools

Python

Job description

Referment is seeking a technically oriented strategist to join a portfolio strategy team that develops active equity and multi-asset investment products for institutional clients. You will combine quantitative research, portfolio design, risk analysis, and client communication to help refine investment products and strategies.

You will work closely with portfolio strategy and investment colleagues to explore enhancements, implement robust models, and present findings to both quantitative and