Freelancer profile translated to English.
Back to original languageAbout Vincent
Doctor in Physics, with significant programming experience (20 years) and consulting (14 years, since 2006) on advanced scientific topics, with training from Centrale Supelec - OpenClassrooms in data sciences, I have recently worked on several strategic projects:
1°) Development of a machine learning algorithm for predicting financial prices,
2°) Dynamic pricing for a hypermarket,
3°) Audit of pricing algorithms of a major bank,
4°) Analysis of a consumer network for targeted marketing,
5°) Development of an advanced erroneous data detection engine.
Using data science tools, I can help you extract and visualize relevant data, identify flaws or anomalies, and ultimately define targeted actions to improve your business. By mathematizing your objectives and constraints, I can rationally formalize your strategy problems and search for the best accessible solutions based on available data. You will then have optimal solutions by taking advantage of the latest advances in machine learning methods and artificial intelligence.
My experience, my initial training in theoretical physics, and intensive calculations on the CNRS supercomputers, also allow me to assist you in auditing, rationalizing, redesigning, accelerating, or improving your algorithms (in Python, R, Matlab, Java, C++ or other languages).
English
Fluent
French
Native or bilingual
Can work on-site
Paris 7e Arrondissement (up to 50km), Paris (up to 100km), Caen (up to 100km)
Experience
- Atout FranceR&D I.A. DirectorPUBLIC SECTORAugust 2021 - February 2022 (7 months)Paris, FranceAutomation of reporting and the recommendation and forecasting system for tourist flows of Atout France using a Web application and artificial intelligence algorithms (Management of a team of 2 AI engineers for automation and R&D in AI).Forecasting tourist flows in France. Integration of the effects of COVID, seasonality, travel searches within search engines, traveler reviews... using deep learning networks in Python/Keras (CNN, LSTM...)Performance: 3 months of reliable forecasting with a margin of error of 10 to 15%
- La Compagnie Generale de ParisHead of R&DE-COMMERCEFebruary 2021 - December 2021 (11 months)Paris, FranceDirector of the data scientists team to develop an AI capable of identifying fraudulent e-commerce sites and a price comparison tool for all products available online.Performance: 99.7% fraud detection
- Air LiquideData Scientist for Innovation & Growth Strategy TeamCHEMICALApril 2019 - September 2019 (6 months)Paris, FranceDesign of new business model, with the objective of providing a first illustration of final deliverables, possibly on a different country than the target deployment country. It help business team refine the analysis and visualisation they need to support their decision making.● Formulate and iterate over hypothesis with business team● Set-up back-testing methodology● Run first simulations of impact on revenues and profitability if x% of customers would have turned to the new revenue model with different price points● Visualisation of resultsIterate over back-test tool on target country and refined business model. The objective is to benchmark different business models with different price points regarding their impact on revenues and profitability.● Integrate target countries data (2 different countries)● Implement back-testing methodology as specified during PoC● Collaborate with business teams to help compare scenarios and recommend price points● Visualisation of resultsA quantitative survey will be run to a sub-segment of customers to evaluate their appetence and willingness to pay for the different business models. Results may require an update with fine-tuned parameters of the simulations.● Final refined simulations with fine-tuned parameters
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Education
- Doctorat de PhysiqueUniversité Pierre et Marie Curie2005Formation en mathématiques et en physiques pour faire de la recherche. Ma thèse porte sur des simplifications de l'équation de Schrödinger en mécanique quantique pour parvenir à simuler numériquement et à mieux comprendre l'interaction laser-matière. Cette formation m'a permis de développer des aptitudes en algorithmique, en modélisation mathématique et en réflexion conceptuelle, avec des chercheurs de premier plan.
- Ingenieur Data ScientistCentrale SupélecLa formation de Centrale Supélec me permet de maitriser les algorithmes d'apprentissage automatique (supervisé / non supervisé). C'est une formation, outre les cours théorique, porte sur la réalisation de 8 projets professionnel de data scientist.