Freelancer profile translated to English.
Back to original languageAbout Thomas
We hear that "Data is the new oil" everywhere and AI sounds like a promise of magical growth, but in practice, it's a bit more complicated than that.
I am Thomas, Lead Data Scientist, and I am committed to using my data analysis expertise to provide concrete solutions to the problems encountered by the companies I work with.
If that sounds vague, let's make an appointment to discuss it. There is today an infinite field of application for Data and each Data Scientist has their area of expertise.
I mainly work on Marketing & Supply Chain issues for the Sport, Finance, Hospitality, and F&B sectors.
I also sometimes work with R&D teams for the creation and implementation of POC models.
Finally, I am also an expert in Open Source Intelligence (OSINT).
French
Native or bilingual
English
Fluent
Can work on-site
Saint-Maur-des-Fossés (up to 10km), Paris (up to 10km)
Experience
- Animaj
On Malt
Audio Features Data AnalysisOctober 2023 - October 2023 (1 month)Paris, FranceAd-hoc analysis of YouTube video features in the children's nursery rhymes domain.Correlation between features and watchtime.Extraction and analysis of audio features on Spotify to determine the characteristics of Top50 songs. - BloomR&D Data ScientistSOCIAL NETWORKSDecember 2021 - September 2022 (9 months)Paris, France- Creation of the architecture and deployment of a "Labs" platform for the R&D team (AWS - CI/CD via GitLab)- Development and deployment of an alerting model for unusual events- Optimization and refactoring of POC projects for deployment on the Labs platform in Python and Spark.- Development of a model to detect weak signals based on the impact of actors. Grouping and monitoring of actors based on their behaviors.
- Nike Retail B.V.Data Scientist - Digital Partners / EcommerceRETAIL (LARGE RETAILERS)August 2017 - November 2019 (2 years and 4 months)Amsterdam, Netherlands- Development of a sales prediction algorithm for 50 iconic footwear models ($1B EMEA demand) using internal signals (sales, marketing efforts) and external signals (social media).- Optimization of seasonal collections by predicting the commercial success of products based on their design and visual attributes.- Improvement of storage costs and quarterly target steering by modeling price elasticity and optimizing the relationship between the discount percentage offered on a product and the number of sales.
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Education
- Master - Concentration in Applied EconometricsESSEC2017Statistics and Econometrics: • Time Series Modeling and Forecasting • Financial Econometrics • Introduction to Econometrics • Forecasting & Predictive Analytics • Marketing Analytics Business Administration: • Corporate Finance • Marketing Management • Business Computing • Managerial Accounting