Senior Quant Strategist, Marquee Platform

Goldman Sachs (lateral); New York (NY); On-site; USD 150,000 - 300,000; Full time

Job summary

Goldman Sachs is seeking a Senior Quantitative Engineer for the Marquee Portfolio Analytics team in New York. You will design, implement, and scale factor risk models, portfolio attribution, and optimization methods within a production analytics platform.

Lead a global engineering team, mentor across time zones, and communicate complex quantitative ideas to senior stakeholders and institutional clients, while advancing CI/CD, testing, and robust data architecture.

Qualifications

• Master's or PhD in a highly quantitative field (e.g., Financial Engineering, CS, Math, Physics, Statistics).
• 5+ years in quantitative research, engineering, or financial modeling at senior level.
• Deep expertise in financial markets, esp. equity, with factor risk modeling and portfolio optimization knowledge.

Responsibilities

• Quantitative model development: design, implement, and scale factor risk models, attribution, and optimization.
• Platform architecture: build scalable data models and real‑time calculation environments.
• Engineering leadership: mentor a global team across regions/time zones and promote technical excellence.
• Stakeholder & client collaboration: explain quantitative ideas to senior stakeholders and external clients.
• Product strategy execution: translate client feedback into production features with PM/UX/Engineering teams.
• Production integrity: enforce CI/CD, testing, and code reviews for robust analytics.

Skills

Leadership

Communication

Cross-timezone collaboration

Mentoring

Education

Master's or PhD in quantitative discipline

Tools

Python

Java

Job description

Goldman Sachs is seeking a Senior Quantitative Engineer for the Marquee Portfolio Analytics team in New York. You will design, implement, and scale factor risk models, portfolio attribution, and optimization methods within a production analytics platform.

Lead a global engineering team, mentor across time zones, and communicate complex quantitative ideas to senior stakeholders and institutional clients, while advancing CI/CD, testing, and robust data architecture.