Freelancer profile translated to English.
Back to original languageAbout Nicolas
Overview
Passionate aboutAIand **Data**, I have spent the last 6 years transforming ideas into concrete and impactful solutions, evolving in various sectors.
My journey began with a major challenge: contributing to the creation and launch of Orange Bank. For 3 years, I learned to structure **complex projects**, leveraging Data to optimize banking services. This experience was a springboard to even more technical and strategic projects.
Subsequently, I joined an HR Tech startup, where I put my skills inMachine Learningand Data to the service of an innovative solution focused on talent management. In parallel, I worked with L'Oréal to **industrialize machine learning models**, proving my ability to transform prototypes into robust and scalable tools.
Recently, I foundedAittia**, a platform dedicated to competitive analysis. I designed and implemented the entire **backendof the platform, managedthe integration of third-party APIs**, and handled all **deploymentsto ensure a reliable and scalable infrastructure. This project embodies my vision: to empower companies to better understand their customers and their market, through simple and powerful tools.
Key skills
- Natural Language Processing (NLP): Expertise in analyzing and leveraging textual data.
- Backend development: Complete design and implementation of robust backend architectures (Python, Django).
- Deployment and infrastructure: End-to-end management of deployments, ensuring reliable and scalable solutions.
- Data and AI: Industrialization of machine learning models and leveraging data for strategic insights.
- Project management and innovation: From large companies to startups, I design tailor-made solutions adapted to each need.
English
Fluent
French
Native or bilingual
Remote only
Primarily works remotely
Experience
- AittiaCo-founder/CTO AittiaCONSULTING AND AUDITSFebruary 2024 - Today (2 years and 4 months)Paris, FranceI designed and implemented the entirebackendof the platform, managed theintegration of third-party APIs**, and handled all **deploymentsto ensure a reliable and scalable infrastructure.This project embodies my vision: to empower companies to better understand their customers and their market, through simple and powerful tools.We help companies make the most of digital with effective, economical and personalized solutions.# Resource optimization:Simplify your processes with our turnkey analyses and strategic recommendations. Free up your teams to focus on what really matters.# Data exploitation:Transform your data into concrete decisions with advanced analysis tools, allowing you to adjust your campaigns with precision.# Complete market vision:Stay ahead with our trend studies, sector comparisons and opportunity identification.-> Observatory of your market# Personalized support:Benefit from tailor-made monitoring to achieve your specific objectives and obtain concrete results.-> Generation of expert reports based on our competitive data
- Orange BankLead ML EngineerBANKING AND INSURANCEOctober 2022 - February 2024 (1 year and 4 months)Machine Learning
- Implementation of good code and code sharing practices
- Benchmarking of solutions (stress-testing, cost vs performance)
- Development of an emotion and age analysis brick
- Implementation of LLM locally
Management- Project management and implementation of Rasa with international teams
- Management of several people on machine learning topics
- L'Oréal SA - L'Oréal FranceML Engineer / Python DeveloperFASHION AND COSMETICSOctober 2021 - October 2022 (1 year)Saint-Ouen, France(BigQuery, Google Cloud Storage, Kubeflow, Python, FastAPI, Docker, Github)ObjectiveIndustrialization of code and processes in a research project including machine-learning solutions.Product GoalProvide a prediction and recommendation tool to the R&I laboratory teamsAchievementCreation of data processing to meet business rules (compliance with certain rules related to chemistry)Adding algorithms to the APIRefactoring of existing code on clean code principles (testing, typing, documentation)Writing project documentation (summary of objectives, participants, API usage, listing of algorithms, rules associated with each functionality, how to contribute, test, debug)Putting the API and models into production via docker image upload.
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Education
- Ingénieur informatique - Spécialité Intelligence ArtificielleÉcole Internationale des Sciences du Traitement de l’Information Génie des Systèmes d’information2019L'enseignement est organisé autour de quatre axes : deep learning, natural language processing, optimisation métaheuristique, algorithmic fairness. Des notions complémentaires sont également enseignées (programmation réactive, calcul GPU-TPU, traitement d'images), ainsi que des cours innovants qui préfigurent l'évolution de l'informatique (informatique quantique, bioinformatique...). Le dispositif pédagogique est enrichi par des séminaires animés par des professionnels et basés sur des études de cas. - Deep Learning : réseaux de neurones, réseaux convolutifs, réseaux récurrents, apprentissage par renforcement - Natural Language Processing : morphologie, lexique, syntaxe, sémantique, grammaire, word2vec, deep learning Optimisation métaheuristique : problèmes de transport, problèmes d’ordonnancement, problèmes sous contraintes, problèmes multi-objectifs, algorithmes multi-agents - Algorithmic fairness - Bioinformatique - Informatique Quantique - Traitement d’image - Calcul GPU-TPU - Programmation réactive - Méthodologie de la recherche scientifique
Certifications
- Big Data Modeling and Management SystemsUC San Diego2021