Candriam is a global multi-specialist asset manager and a recognized pioneer and leader in sustainable investment. For more than 25 years, Candriam has offered innovative and diversified investment solutions across many asset classes including fixed income, equities, absolute return , asset allocation and illiquid assets.

As a Responsible Employer, Equal Employment Opportunity is crucial to Candriam. We are committed to building the best global team that represents a variety of backgrounds, perspectives, and skills. We provide an inclusive work environment and support wellbeing and work-life balance.

Join the Fixed Income Quantitative team to contribute to the development of an in-house Machine Learning framework dedicated to the estimation of Fair Value Option-Adjusted Spreads (OAS) in High Yield markets, starting April 2026.
The objective is to address illiquid market conditions and missing data issues in order to support relative value analysis and identify rich/cheap opportunities in Fixed Income strategies.

• Develop and implement Machine Learning models to estimate Fair Value OAS in illiquid High Yield markets.
• Design a Recommender System–based framework to address missing or infrequently updated market data.
• Contribute to the ongoing development of a quantitative infrastructure for Fixed Income strategies involving Machine Learning.
• Extend the existing framework from forecasting strategies to Relative Value strategies.
• Benchmark Machine Learning approaches against traditional pricing methodologies, such as interpolation and peer-based comparisons.
• Apply the methodology to other missing-data use cases, including volatility estimation and credit spread estimation in convertible bonds.
• Analyze model outputs and support the identification of relative value (rich/cheap) opportunities for trading strategies.
• Document methodologies and results to ensure clarity and reusability of the framework.