Über Nicolas
Data scientist depuis 6 ans, j'ai effectué mon post doc en topological data analysis à l'EPFL (Lausanne) où j'ai travaillé sur l'étude de gros graphes du cerveau.
Je me suis ensuite mis à mon compte dans une entreprise de finance décentralisé, en tant que développeur python et data analyste.
J'ai une solide formation en mathématique et informatique.
Französisch
Muttersprachlich oder zweisprachig
Englisch
Verhandlungssicher
Nur remote
Führt Projekte hauptsächlich remote aus
Projekt- und Berufserfahrung
- CNRS (LEGOS)Refactorisation de code d'une application scientifique.September 2024 - Oktober 2024 (2 Monate)- Refactorisation de code python scientifique- Amélioration des performances- Conseil sur des eventuelles incohérences/erreurs dans la pipeline de data- Conseil en design/algorithme
- Stake Capital GroupData AnalystAugust 2021 - März 2023 (1 Jahr und 7 Monate)Blockchain data analyst:I was in charge of multiple and varied tasks mostly centered around our defi and gaming activity:- setting up our data stack, to be used for our frontend, and for analysis (a mix of many tools, mostly the graph)- analyzing blockchain data, user activity, player behavior- smart contract analysis (especially for investment purposes)Python developper:- automation in various domains (day to day activity, gamng, data retrieval)- adding functionality to some existing code base to interact with more dexesSome light experience with aws, react,typescript.
- Ecole polytechnique fédérale de LausannePost DocAugust 2017 - August 2021 (4 Jahre)Lausanne, SchweizI did a postdoc in a team of mathematicians working mainly with the blue brain project. It was a collaboration between computer neuroscientist and mathematician.My research mainly involve doing graph analysis, on big graph coming from the brain model of the rats. We used extensively TDA (topological data analysis) to compute (topological) graph invariant.My work mostly involved using a range of data analysis method and sometimes creating new ones to apply to our "big connectome graph".Base code was almost always python, with some c/c++ code binding when we needed fast computation.Here are a few activities I was involved with:- computing graph invariants (often on supercomputer via slurm)- creating variation of those invariants- applying known method to our data (ie reading neuroscience paper that analyse real data and doing the same on synthetic data to compare)- using a wide range of model depending on the data (from simple regression to random forest, not much DNN as they didnt really suited our use cases)Beside that I also had the usual teaching/mentoring, I taught linear algebra at EPFL mostly TD, supervising a few interns.
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Ausbildung und Abschlüsse
- Phd in computer scienceUniversité Paris Saclay2016I worked on topological models of concurency in the LIX laboratory at the école Polytechnique.
- Agrégation de MathématiqueParis Saclay2012French national examination to be able to teach math.