Senior Quantitative Researcher – Margin & Risk (Python)

Radley James; New York (NY); On-site; USD 500,000 - 600,000; Full time

Job summary

Radley James is partnering with a leading institutional financial platform to recruit a Senior Quantitative Researcher focused on margin methodologies across prime brokerage and clearing. The role entails hands-on research, model design, validation, and integration into live infrastructure.

The candidate will design and enhance models for linear and non-linear products, implement production-grade Python code, and work with cross-functional teams to advance risk frameworks.

Qualifications

• 5+ years of quantitative experience.
• Strong understanding of margin methodologies across linear and non-linear products.
• Hands-on research design, validation and implementation of margin models.

Responsibilities

• Designing and enhancing margin and risk models for clearing and prime brokerage.
• Writing production-quality Python code for model implementation and analytics.
• Conducting independent research into margin methodologies and model improvements.
• Partnering with engineering and business teams to integrate models into live infrastructure.
• Contributing to model validation, documentation, and architecture discussions.
• Direct experience building or replicating prime brokerage margin models (sell-side).

Skills

Python

Statistical modelling

Quantitative analysis

Margin modelling

Risk modelling

Model validation

Prime brokerage

Education

Graduate degree in Mathematics/Statistics/Physics/Engineering/CS

Tools

Python

Job description

Radley James is partnering with a leading institutional financial platform to recruit a Senior Quantitative Researcher focused on margin methodologies across prime brokerage and clearing. The role entails hands-on research, model design, validation, and integration into live infrastructure.

The candidate will design and enhance models for linear and non-linear products, implement production-grade Python code, and work with cross-functional teams to advance risk frameworks.