Quantitative AI Portfolio Engineer (Fixed Income) H/F

Crédit Agricole Group; Saint-Denis; Sur place; EUR 60 000 - 90 000; Plein temps

Résumé du poste

Crédit Agricole Group is seeking an expert in Research & Quantitative Model Development in Saint-Denis, France. The role involves designing quantitative models and machine learning algorithms to generate investment signals across different markets, conducting robust back-testing, and managing the entire model lifecycle.

Ideal candidates will have a strong foundation in quantitative methods, machine learning techniques, and experience in feature engineering. Proficiency in communicating complex technical concepts to non-technical stakeholders is essential.

Qualifications

• Experience in designing and developing quantitative approaches and machine learning algorithms.
• Strong knowledge in feature engineering including macro and market microstructure.
• Familiarity with supervised and unsupervised learning models (regression, classification, clustering).

Responsabilités

• Design and develop quantitative approaches and machine learning algorithms.
• Implement and oversee robust back-testing frameworks.
• Own the full model lifecycle: specification, prototyping, validation, and monitoring.

Description du poste

Research & Quantitative Model Development

• Design and develop quantitative approaches and machine learning algorithms to generate investment signals on interest rates (curve dynamics, term premia, vol, macro linkages), and credit markets (spread dynamics, momentum, carry, liquidity, regime effects).
• Perform advanced feature engineering (macro, market microstructure, flows, liquidity, ESG, sentiment).
• Develop supervised and unsupervised learning models:
  • regression, classification, clustering
  • tree-based models, ensemble methods
  • deep learning architectures (LSTM, Transformers when relevant)
• Integrate alternative and unstructured data (news feeds, central bank communications, broker research, transcripts, regulatory publications).
• Build & maintain a reusable internal library of features, models, preprocessing pipelines, validation tools.
• Collaborate with the research ecosystem (e.g. Amundi Institute) to translate academic innovations into operational investment models.

Back-testing & Validation

• Implement and oversee robust back-testing frameworks addressing biases (look-ahead, survivorship), transaction costs, liquidity constraints and slippage.
• Perform deep robustness analysis via stress tests, walk-forward analysis, bootstrap methods and stability checks across market regimes, including crisis periods.
• Measure risk-adjusted performance of strategies and evaluate sensitivity to macro and market factors.
• Define clear model acceptance criteria, rejection thresholds and degradation metrics.

Engineering & Productionisation

• Own the full model lifecycle: specification, prototyping, validation, industrialization, monitoring and maintenance.
• Implement monitoring and alerting for data drift, model drift and performance decay, and define rollback procedures.

Reporting & Documentation

• Document methodologies, assumptions, validation metrics and production procedures.
• Prepare reports and presentations for senior management, investment committees and client-facing teams.
• Communicate model rationale, risks, limitations, and governance aspects clearly to non-technical stakeholders.
• Actively contribute to model governance, internal audits, regulatory reviews when applicable.