Freelancer profile translated to English.
Back to original languageAbout Julien
Computer Engineering graduate specializing in Big Data, I am passionate about Data Science, Artificial Intelligence, and new technologies. These fields offer the opportunity to engage with numerous business sectors and challenges. That's why I joined Malt to undertake exciting projects and leverage my skills to support you in your new endeavors!
LinkedIn: Julien Roumagnac
French
Native or bilingual
English
Fluent
Can work on-site
Lyon (up to 50km)
Experience
- UbisoftData ScientistVIDEO GAMES AND ANIMATIONSeptember 2022 - Today (3 years and 9 months)Lyon, FranceWorking on In Game player experience personalization & recommendation
- AVISIAConsultant Data ScientistDIGITAL AND ITMarch 2020 - September 2022 (2 years and 6 months)Lyon, FranceAvisia internal roles :○ Lead of a computer vision R&D project: development of a web application to detect & localize specific objects in a picture using Deep Learning○ GCP Machine Learning Engineer instructor: co-creation of a study path for the certification (main resources, milestones, trainings necessary to be ready for), co-animation of training sessions, mentoring participants during the process○ Contributor: Participation in internal streams to present technical subjects, feedback, etc., and internal articles writingWithin the DATA & AI Lab of a major player in fashion and luxuryMissions :Scoring Categories of Interest (Machine Learning):○ Development of Machine Learning algorithms for scoring customer appetite for different defined product categories○ Analysis of the model with XAI methods (AI Interpretation) to allow business teams to understand the algorithm's decisions○ Development of a model training/scoring/monitoring pipeline○ Analysis and monitoring of prediction results, comparing it to traditional methods.○ Automation of this pipelineEmailing optimization (Deep Learning):○ Implemented a product recommendation algorithm for the customer's next purchase for an email prioritization context to select the most relevant emails for each customer○ Development of the algorithm based on an LSTM architecture○ Development of Dataiku training & scoring flows○ Development of a Dash web app to allow business teams to easily interact with the algorithm○ Development of the first Dataiku use case of the company => participation in various tests and reflection on the implementation, use, and governance of the tool for future projectsElaboration of ML Engineering / ML Ops best practices:○ In collaboration with the Lead ML Engineer:○ Realization of workshops to define the ML Ops needs of the team.○ Definition of the best practices to be implemented○ Design of the generic ML ops architecture for the Lab's ML projects○ Application of this architecture to my project Categories of interest○ Coaching other Data Scientists to implement this architecture on their projectsAnalysis and specific developments :○ Analysis and understanding of the customer base○ Study of available data sources (customer data, web browsing, and social networks)○ Statistical analysis and cross-referencing of data sources○ Data processing and cleaning, creation of DataMarts dedicated to analysis○ Definition of KPIs in collaboration with the Business Analyst○ Development of customer segmentation and analysis methods based on KPIs○ Development of a Machine Learning algorithm for scoring the appetite of customers for the purchase of a 1st "ready to wear" purchase during the next month.
- VOLPI IMMOBILIERData ScientistREAL ESTATEAugust 2020 - September 2020 (1 month)Lyon, France#Python #MachineLearning #Scikit-learn #Xgboost #pandas #API #Flask #Pickle-> Creation of a real estate property value estimator:• Feasibility study and project scoping• Data source analysis• Statistical analysis and data processing• Construction of the study database• Development and optimization of a regression algorithm• Compression of the algorithm for production use• Deployment of the estimation algorithm via a Flask API• Creation of a routine to regularly update the algorithm to account for new available data
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Education
- Computer Engineering, Big Data specializationPolytech Montpellier2020