Global Quant Research Lead — Risk & Model Analytics

ICE; Greater London; On-site; GBP 60,000 - 80,000; Full time

Job summary

ICE is seeking a Quantitative Analyst to join the Global Quantitative Research Group, focusing on model development and risk analytics. The role involves leading R&D for margin and risk management models, conducting data analysis, and building data-driven software solutions.

Ideal candidates will have an advanced degree in a relevant field, strong programming capabilities in Python and SQL, and a solid grasp of financial derivatives. Collaboration with cross-functional teams is essential.

Qualifications

• MSc or PhD in Mathematics, Statistics, Physics, Quantitative Finance, or Data Science.
• Experience in quantitative finance or data science preferred.
• Strong programming skills in Python and SQL.
• Working knowledge of relational databases and version control tools.
• Solid understanding of financial derivatives pricing and risk management.

Responsibilities

• Lead R&D of margin, stress testing, and risk management models.
• Conduct quantitative risk analysis across multiple asset classes.
• Build production-quality software solutions for model implementation.
• Develop ETL pipelines for financial datasets.
• Document and present findings to stakeholders.

Skills

Quantitative analysis

Programming in Python

SQL proficiency

Statistical analysis

Financial derivatives knowledge

Education

Advanced degree in Mathematics, Statistics, Physics, or related field

Tools

Python

SQL

R

MATLAB

C++

Java

Oracle

Postgres

Snowflake

Git

Job description

ICE is seeking a Quantitative Analyst to join the Global Quantitative Research Group, focusing on model development and risk analytics. The role involves leading R&D for margin and risk management models, conducting data analysis, and building data-driven software solutions.

Ideal candidates will have an advanced degree in a relevant field, strong programming capabilities in Python and SQL, and a solid grasp of financial derivatives. Collaboration with cross-functional teams is essential.