Description

Quantitative Finance & AI Engineer | LLM Agents, Portfolio Optimization & Risk

I am a quantitative finance and AI engineer specializing in AI-driven decision systems for financial markets, with a focus on LLM-powered agents, portfolio optimization, and risk analytics.

I hold a MSc in Technology & Management from CentraleSupélec and a Master’s degree in Financial Markets, with solid training in mathematics, portfolio management, and machine learning.

I currently work as a Quantitative Researcher for a London-based fintech, where I design and implement AI-assisted allocation and research systems. My work combines deterministic optimization, machine learning, and LLM reasoning to build robust, explainable, and production-ready financial tools.

I design LLM-powered agents to orchestrate quantitative workflows such as portfolio construction, stress testing, model comparison, and research reporting, while enforcing strict risk, governance, and reproducibility constraints. My focus is on AI systems that meet institutional finance standards rather than black-box prototypes.

On the quantitative side, I have built:

portfolio optimization engines with CVaR, Expected Shortfall, drawdown, sector and turnover constraints,
point-in-time backtesting frameworks with transaction costs and regime analysis,
reproducible research environments using Docker and testing.

Previously, I spent two years at BNP Paribas CIB in Product Management, developing tools for collateral optimization, scenario generation, and regulatory risk analytics.

Services

AI & LLM agents for finance and decision-making
Quantitative research and portfolio optimization
Backtesting, risk analytics, and stress testing
Machine learning applied to financial markets
Python-based research-to-production tooling

Tech stack

Python, pandas, NumPy, scikit-learn, TensorFlow, LLM APIs, cvxpy, SQL, Docker, Git, Bloomberg.

I work remotely with clients in Europe, the UK, and globally.

Langues

Français
Bilingue ou natif
Anglais
Bilingue ou natif

Préférences en matière de lieu de travail

En télétravail uniquement

Travaille majoritairement à distance

BANQORA LTD
Quantitative Researcher
CAPITAL-INVESTISSEMENT
septembre 2025 - Aujourd'hui (9 mois)
London, UK
• ▪ Engineered and productionized a proprietary portfolio optimization engine integrating advanced risk controls (CVaR, Economic Drawdown, sector and turnover constraints) with AI-assisted rebalancing, tailored for institutional mandates.
• ▪ Designed and validated a cutting-edge, point-in-time backtesting framework with rolling windows, comprehensive transaction cost modeling, and robust regime segmentation (e.g., COVID crisis), enabling scientific performance evaluation and model governance.
• ▪ Delivered a reproducible quant research platform using Docker-based containerized dev environments and automated
in-image testing, cutting setup time and eliminating environment drift for collaborators.
• ▪ Led the development and benchmarking of allocation agent frameworks powered by LLM reasoning and systematic optimizers, achieving documented improvements in forward-looking Sharpe, drawdown control, and statistical
outperformance versus ETF benchmarks over multi-year periods.
• ▪ Designed and implemented a multi-year, macro-driven stress testing framework combining regime-switching scenario
generation, factor-based loss models, liquidity/FX modules and capital/liquidity impact analytics.
LLMs Machine Learning/AI in investments backtesting Machine Learning Python Développement et évaluation de modèles
BNP PARIBAS CIB
Quantitative Derivatives Management Apprentice
BANQUE & ASSURANCES
septembre 2021 - août 2023 (1 an et 11 mois)
93500 Pantin, France
• ▪ Developed Python-based quantitative tools to optimize collateral allocation for OTC and listed derivatives, implementing economic scenario generation models (Monte Carlo, stochastic interest rate models) to enhance risk management and
regulatory reporting.
• ▪ Optimized Solvency II structuring for 40+ clients by accurately classifying portfolios and calibrating SCR for complex derivatives (e.g., FX swaps), while collaborating with Sequantis to enhance risk optimization models and integrate data
sharing solutions using the internal Manaos platform.
Analyse exploratoire des données Project Management Risk Management Regulatory Reporting Modélisation financière
OFI INVEST ASSET MANAGEMENT
Credit Research Analyst – Summer Intern
CAPITAL-INVESTISSEMENT
février 2021 - avril 2021 (2 mois)
Paris, France
• ▪ Performed in-depth fundamental credit analysis and issuer rating assessments on corporate issuers across the automotive
(Magna), pharmaceutical, and diversified sectors (Lagardère), using Bloomberg, financial reports, earnings calls, and sell-side research.
• ▪ Applied Excel-driven DCF models to forecast issuer fundamentals and assess potential impact on credit spreads and sector performance, and recommended investment strategies (hold, sell, buy) to portfolio managers based on analysis outcome.
Modélisation financière Risque de crédit DCF Analyse financière Analyse Diagnostic Recommandations