Quantitative Analyst Intern F
il y a 5 jours
Description du poste Métier Investment Management - Fixed Income Intitulé du poste Quantitative Analyst Intern F / M Contrat Internship Durée du contrat 6 months internship Présentation de Candriam Group 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. Mission 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. Responsabilité 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. Profil Preparing a Master's degree in Quantitative Finance, Data Science, Computer Science, Engineering, or a related field Strong analytical and synthetic mindset, proactive and autonomous Good knowledge of programming languages, in particular Python (SQL is a plus) Proven interest or experience in Machine Learning and quantitative modeling Solid foundations in statistics, machine learning and data analysis Good understanding of Fixed Income markets and interest in quantitative finance Knowledge of Excel / VBA is a plus Fluent in English and French (written and spoken) #J-18808-Ljbffr
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