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Research Scientist (QA & ML), Rates Algorithmic Trading Strategies
I am a Data Scientist mainly focussed of new Theoretical Machine Learning methods but always keeping in mind practical applications and implementations. I am particularly interested in tackling Game theory derived Learning problem (That's why I work in Finance !) and social sciences issues in AI. Now what's really matter! I am a cinema addict, for those speaking French if you really want to know me: check my profile flaviiiii on Télérama'Vodkaster
New York University
The Courant Institute School of Mathematics, Computing, and Data Science, Master of Science Mathematics in Finance, Advanced Machine Learning and Deep Learning Track
January 1, 2016 – January 1, 2018
ESSEC Business School
"Programme Grande Ecole", Master of Science in Management
January 1, 2014 – January 1, 2018
Pierre and Marie Curie University
Unités d'Enseignement Isolées du Master Mathématiques et Applications
January 1, 2014 – January 1, 2015
ENSAE Paris
"Cursus Ingénieur", Majeure Mathématiques Appliquées, 3A Data Science: voie Machine Learning
January 1, 2011 – January 1, 2016
Toulouse School of Economics
Licence Mathématiques et Economie, M1 Economie et Statistique (voie recherche)
January 1, 2011 – January 1, 2013
Lycée Pierre de Fermat
Classe Préparatoire aux Grandes, Mention Très Bien
January 1, 2009 – January 1, 2011
Barclays
Director, Rates Algorithmic Trading Strategies, Research Scientist (QA & ML)
January 1, 2024 – Present
Barclays
Vice President, Rates High Frequency Trading, Research Scientist (QA & ML)
January 1, 2021 – December 1, 2023
Barclays
Assistant Vice President, Machine Learning Research - Rates Algorithmic Trading
July 1, 2018 – December 1, 2020
Lake Hill Capital Management
Recherche Quantitative, Stagiaire
June 1, 2017 – August 1, 2017
New York City Metropolitan Area
Credit Suisse
Analyste Quantitatif Stagiaire (Data Science), SMG (devenu Qube Research & Technologies)
May 1, 2016 – August 1, 2016
Natixis Asset Management
Analyste Quantitatif Stagiaire, Direction Strategies Taux
April 1, 2015 – September 1, 2015
Paris, France
ESSEC Business School
Assistant de Recherche, Series Temporelles Financière
October 1, 2014 – January 1, 2015
Cergy-Pontoise, France
Natixis
Chargé d'Etude Statistique (stage)
June 1, 2012 – August 1, 2012
Paris, France
High Frequency Trade & Quote Data analysis for Building Market Impact model (Almgren Chriss framework) in Java
January 1, 2017 – Present
Extra project in the course Algorithmic Trading & Quantitative Strategies in order to work deeper on Tick Data: Implementing an efficient way to process data (100's GB) and estimating Almgren Chriss Market Impact model
Optimal order split across Dark Pools
April 1, 2016 – Present
- Studied and implemented a Stochastic Optimization (Python) - Studied of an alternative approach by Reinforcement Learning
Compressed Sensing MRI Reconstruction
February 1, 2016 – Present
Implementation of reconstruction algorithm of subsampled MRI k-space by sparsity property (wavelet domain) with Convex Optimization algorithms (Python)
Automated Vehicle trajectory prediction by multi-sensors data fusion (GPS, Radar and Laser) with sensor failure detection
November 1, 2015 – Present
Defined State Space Model of an automated vehicle and estimated make system predictions via multi-sensor data fusion (GPS, Laser, Radar) with sensor failure detection by Bayesian Network models Utilized Unscented Kalman Filter, Bayesian Particle Filtering algorithm and sequential Monte Carlo to provide failure robust estimation and forecasting of the trajectory
Path Finder Software for Paris Subway
February 1, 2014 – Present
Developed in C++ of a software to find optimal paths in Paris Subway Contents: - Implemented Dijkstra algorithm to find optimal path - Designed a graphic interface for algorithm visualization
Cultural Fit Analysis
The candidate's background in both finance and advanced mathematics/data science, coupled with diverse project experience (algorithmic trading, MRI reconstruction, vehicle trajectory prediction), suggests adaptability and a broad intellectual curiosity. Their continuous progression in a demanding financial environment like Barclays indicates resilience and a results-oriented approach, which generally aligns with high-performance cultures. The academic rigor and practical application of complex models suggest a strong fit for roles requiring deep analytical thinking and innovation.
Soft Skills & Operational Fit
The candidate's project descriptions and work history suggest a strong analytical mindset, problem-solving capabilities, and a research-oriented approach. The progression through roles at Barclays from AVP to Director indicates strong performance and leadership potential. The focus on quantitative strategies and data-driven decision-making aligns well with operational needs for a Data Analyst.