SVP, Market Risk Quant — Bond Analytics Lead (Hybrid)

Jefferies; Greater London; Hybrid; GBP 80,000 - 120,000; Full time

Job summary

A leading financial services firm in the UK is seeking a proven leader in market risk analytics to spearhead the development of their next-generation bond analytics library. This pivotal role will focus on enhancing fixed income risk management capabilities and involve leading model development and mentoring junior team members. The ideal candidate has extensive experience in quantitative risk analytics, a strong command of Python, and a deep understanding of structured products. This position offers a competitive compensation package and a flexible hybrid work environment.

Benefits

Competitive compensation package

Comprehensive benefits

Work-life balance

Qualifications

• 7+ years of experience in quantitative risk analytics and technology leadership.
• Successful in building and leading risk analytics/modeling teams.
• Deep knowledge of market and credit risk, structured products, and regulatory frameworks.
• Advanced proficiency in Python and quantitative/statistical modeling.
• Exceptional communication, leadership, and mentoring skills.

Responsibilities

• Lead the implementation of the bond analytics library and oversee model development.
• Architect and maintain quantitative libraries for production.
• Collaborate with cross-functional teams to align solutions with business objectives.
• Mentor and develop junior team members in technical excellence.

Skills

Quantitative risk analytics

Financial modeling

Leadership

Python programming

Statistical modeling

Communication skills

Education

Advanced degree in a quantitative field (Finance, Engineering, Mathematics)

Tools

AWS

Azure

Job description

A leading financial services firm in the UK is seeking a proven leader in market risk analytics to spearhead the development of their next-generation bond analytics library. This pivotal role will focus on enhancing fixed income risk management capabilities and involve leading model development and mentoring junior team members. The ideal candidate has extensive experience in quantitative risk analytics, a strong command of Python, and a deep understanding of structured products. This position offers a competitive compensation package and a flexible hybrid work environment.