Lionel Ouaknin is a quantitative analyst based in Paris with nine years of hands-on experience building and validating market and solvency risk models across major French financial institutions. He specializes in risk metrics, parameter estimation and calibration (SABR, Hull-White, Monte Carlo VaR) and leverages the Python ecosystem (cvxpy, scikit-learn, Keras) to productionize analytics for structured rates and regulatory solvency. His background spans market risk, model validation and econometrics roles at Groupe Caisse des Dépôts, SFIL, Natixis and Société Générale, giving him deep familiarity with both trading instruments and prudential frameworks. Comfortable moving between research and implementation, he combines statistical rigor with pragmatic coding to deliver auditable, model-driven risk solutions. An engineer by training, he often bridges quantitative modeling and software-oriented automation to accelerate calibration and reporting workflows.
9 years of coding experience
Génie Informatique et Statistiques, Mathematics and Computer Science, Génie Informatique et Statistiques, Mathematics and Computer Science at Polytech'Lille
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