Markets Quantitative Analyst: Capital Analytics

eFinancialCareers; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Professional development

Hybrid working model

Collaborative environment

Competitive compensation

Job summary

Citi is seeking a highly skilled quantitative analyst to build and optimise cross-asset models influencing trading decisions. You will develop analytics that improve capital deployment and risk-adjusted returns across global markets.

The role involves advancing modeling techniques, collaborating with traders and analysts, and delivering scalable Python/C++ solutions in a hybrid working environment. Candidates with strong academic credentials are prized.

Qualifications

• Strong quantitative background with advanced mathematics or related field.
• Experience developing quantitative models and analytics in financial markets.
• Strong programming skills in Python and/or C++.
• Solid understanding of probability, statistics, numerical methods, and financial modelling.

Responsibilities

• Develop and enhance cross-asset quantitative models used to measure and optimise capital across global trading businesses.
• Build analytical frameworks supporting pricing, balance sheet optimisation, and capital-efficient trade structuring.
• Partner with traders, structurers, and quantitative analysts to deliver actionable insights for front-office decisions.
• Design and implement scalable Python and C++ analytics used across trading, risk, and capital management platforms.
• Work on large datasets and complex portfolios to improve modelling accuracy and efficiency.
• Contribute across the full model lifecycle from research to production support.

Skills

Quantitative background

Python

C++

Statistics

Communication

Education

Master's/PhD in a quantitative field

Tools

Python

C++

Job description

Citi is seeking a highly skilled quantitative analyst to build and optimise cross-asset models influencing trading decisions. You will develop analytics that improve capital deployment and risk-adjusted returns across global markets.

The role involves advancing modeling techniques, collaborating with traders and analysts, and delivering scalable Python/C++ solutions in a hybrid working environment. Candidates with strong academic credentials are prized.