Credit Quantitative Analyst: Alpha Modeling & Research

Logansinclair; Greater London; On-site; GBP 60,000 - 90,000; Full time

Job summary

Logansinclair is seeking a Quantitative Analyst based in London to enhance alpha research and model development across credit markets. This role requires a strong grasp of quantitative methodologies and experience in building credit models. Candidates should have expertise in Python, SQL, and data analysis tools, along with excellent communication skills to collaborate effectively across teams. The position offers opportunities to contribute to a global asset manager with a leading systematic credit capability.

Qualifications

• BSc/MSc in a quantitative discipline; strong statistics, econometrics, and numerical methods.
• Proven track record building quantitative models in an investment or credit context.
• Experience handling large, complex financial datasets.

Responsibilities

• Develop quantitative credit models, including spread and default risk frameworks.
• Source, test, and integrate new alpha signals across credit markets into research pipelines.
• Monitor model-generated trade ideas and disseminate outputs to investment teams.
• Build and maintain the research platform and shared analytical codebase.
• Translate quantitative insights for Portfolio Managers, Credit Analysts, Traders, and Investment Directors.

Skills

Strong statistics

Econometrics

Numerical methods

Strong Python (pandas, NumPy)

SQL

Git

Advanced Excel

Clear communication of technical concepts

Collaborative and adaptable

Education

BSc/MSc in a quantitative discipline

Tools

Excel

Bloomberg or similar data platforms

Job description

Logansinclair is seeking a Quantitative Analyst based in London to enhance alpha research and model development across credit markets. This role requires a strong grasp of quantitative methodologies and experience in building credit models. Candidates should have expertise in Python, SQL, and data analysis tools, along with excellent communication skills to collaborate effectively across teams. The position offers opportunities to contribute to a global asset manager with a leading systematic credit capability.