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Long short systematic credit quantitative researcher – asset manager

Bedford
Octavius Finance
Quantitative researcher
Posted: 24 April
Offer description

Octavius Finance are a specialist hedge fund and asset management recruitment firm, working with leading investment managers across public and private markets. Octavius Finance are recruiting for a Credit Quantitative Researcher on behalf of a London-based asset manager specialising in credit investing, long/short credit strategies, and credit hedge fund investing across global credit markets, with a primary focus on European credit.

This Credit Quantitative Researcher role sits within a credit investment team covering corporate bonds, leveraged loans, and structured credit instruments such as CLOs.

Key Responsibilities:

* Develop, implement, and maintain quantitative models for credit relative value, pricing, and risk analysis across cash and structured credit markets
* Build factor-based and statistical models for credit spread dynamics, default risk, and recovery assumptions
* Analyse large, complex datasets across corporate bonds, leveraged loans, CDS, and structured credit products (including CLO tranches)
* Support portfolio construction, optimisation, and trade idea generation across long/short credit strategies
* Develop tools for risk monitoring, stress testing, scenario analysis, and performance attribution
* Enhance pricing and valuation frameworks for illiquid or complex credit instruments
* Work closely with portfolio managers and analysts to translate quantitative outputs into actionable investment insights
* Contribute to automation and improvement of research workflows and data pipelines
* Research and prototype new quantitative approaches for credit investing, including machine learning and alternative data applications

Requirements:

* Degree in a highly quantitative discipline (e.g. mathematics, physics, engineering, statistics, computer science, finance, econometrics)
* Experience in credit markets, fixed income, or structured credit strongly preferred
* Strong programming skills in Python (or equivalent), with experience in data analysis libraries (e.g. pandas, NumPy, SciPy)
* Good understanding of credit products including corporate bonds, leveraged loans, CDS, and CLO structures
* Knowledge of statistical modelling, time series analysis, and machine learning techniques beneficial
* Familiarity with risk modelling, portfolio construction, or quantitative trading strategies
* Experience working with large financial datasets and building robust research pipelines
* Strong analytical mindset with ability to work with incomplete or noisy financial data
* Excellent communication skills and ability to work collaboratively within an investment team
* Strong interest in global credit markets and alternative investment strategies


To apply, please submit a copy of your word CV to

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