Loïck Vidot

Après un diplôme d'ingénieur en statistique obtenu en 2016 à l'ENSAI (Ecole Nationale de la Statistique et de l'Analyse de l'Information) et suite à 7 années d'expérience professionnelle en tant que Statisticien au sein d'un laboratoire pharmaceutique, je suis actuellement en reconversion professionnelle pour appliquer mes compétences dans le domaine du Sport.

J'ai intégré le Master of Science “Data analytics in football” en Octobre 2023 et en parallèle, j'occupe un poste de Data Scientist stagiaire au sein du Pôle Olympique de la Fédération Française de Badminton depuis Février 2024.

Je suis ainsi ouvert aux opportunités d'emploi pour des postes de Data Scientist / Data Analyst dans le milieu du Sport.

Data Scientist Intern at French Badminton Federation (Feb 2024 - Today)

• Conception of a relational database for historical data storage (i.e., player rankings, tournament results, match scores) (Azure Data)
• Automatisation of a process and scripts for weekly database updates (R)
• Collaboration on the development of a platform dedicated to sports and performance direction (Python – dash) with multi-functionalities such as:

Follow-up and athlete monitoring (e.g., current physical condition, current ranking, recent tournament results, whole performance trajectories, transit times per ranking thresholds, performance criteria achieved, ...)

Season planner, a planifcation tool to optimize the costs/benefits tradeoff (e.g., costs associated to tournament participation vs expected world ranking points gain)

Senior Biostatistician at Institut de Recherches Internationales Servier (Nov 2016 - Oct 2023)

• Statistical expertise from the conception to the submission of a clinical study in collaboration with the project team:
• Assessment of clinical trial designs options, statistical assumptions definition and number of patients needed computation
• Writing of the statistical section of the clinical study protocols and supervision of Statistical Analysis Plans writing
• Validation of statistical production (SAS/R/R Markdown - survival, survminer)
• Clinical trial study results presentation to the project team (multidisciplinary team) and the partners
• Management of subcontracted activities (e.g., statistical programming) and associated timelines
• Development of statistical methods for the follow-up of a clinical trial (recruitment prediction, events prediction)(R - rstan, survival)
• Development and presentation of Machine Learning algorithms (random forests) on survival data for the identification of discriminant factors (R - randomForestSRC, survival)
• Supervision of a 6-month intern for clinical trials probability of success computation (R - rstan, ggplot2)

• Master of Science Data Analytics in Football - Sports Data Campus (2024)
• Engineering Master Degree in Statistics - ENSAI (2016)