Senior Quant Developer – Derivatives Risk & IMM Analytics

Talensa; Greater London; On-site; GBP 70,000 - 100,000; Full time

Job summary

Talensa is seeking an experienced Quantitative Developer at Associate Director level to enhance their Derivatives risk management. The role requires strong expertise in Python and experience in quantitative development to build risk libraries, validate methodologies, and collaborate with cross-functional teams. Candidates should have a Master’s in a quantitative field and experience in financial services. This opportunity emphasizes robust programming skills, knowledge of risk modelling and analytics, and offers career progression in a leading environment.

Qualifications

• Proven experience in quantitative development within financial services.
• Experience in risk management and derivatives risk is highly desirable.
• Exposure to consulting firm environments or financial institutions.

Responsibilities

• Develop and maintain quantitative libraries for risk calculations.
• Implement and optimize IMM methodology within platforms.
• Collect and validate market and risk data.
• Develop backtesting and performance monitoring frameworks.
• Build and enhance analytics platforms for IMM processes.
• Collaborate with teams to ensure efficient enhancements.

Skills

Python

C++

Java

Pandas

NumPy

SQL

Risk modelling

Derivatives pricing

Education

Master’s degree in Mathematics, Physics, or Computer Science

Tools

Git

Cloud-based solutions

Job description

Talensa is seeking an experienced Quantitative Developer at Associate Director level to enhance their Derivatives risk management. The role requires strong expertise in Python and experience in quantitative development to build risk libraries, validate methodologies, and collaborate with cross-functional teams. Candidates should have a Master’s in a quantitative field and experience in financial services. This opportunity emphasizes robust programming skills, knowledge of risk modelling and analytics, and offers career progression in a leading environment.