Fabien Gadet

Data scientist

Remote from Paris

  • 48.8546
  • 2.3477
  • Indicative rate €500 / day
  • Experience 2-7 years
Propose a project The project will only begin when you accept Fabien's quote.

Confirmed availability

Part time, 2 days a week

Propose a project The project will only begin when you accept Fabien's quote.

Location and geographical scope

Paris, France
Remote only
Works remotely most of the time


Project length
  • ≤ 1 month
  • Between 1-3 months
  • Between 3-6 months




  • Français

    Native or bilingual

  • Anglais

    Full professional proficiency

  • Chinois


Skills (29)

  • Operating system
  • Containerization
  • Languages
  • Beginner Intermediate Advanced
  • Beginner Intermediate Advanced
  • C
    Beginner Intermediate Advanced

Fabien in a few words

Data scientist / engineer depuis 2 ans, j'ai réalisé de nombreux projets autour de la dat autant du coté database, ETL pipeline que du coté analyse et data science .J'ai travaillé pendant 1 an et demi chez Qobuz principalement pour faire des modèles prédictifs afin d'aider à la rétention, conversion des clients et détection de fraude et pour alimenter une data warehouse complète.
(+5 à 10% de rétention supplémentaire suite à la mise en place de mes modèles)J'ai également de l'expérience en web (API, architecture)

Réalisation de plusieurs projets autour de la dat sur mon temps libre (principalement en Julia / Python)



High Tech

Data Scientist

Région de Paris, France

September 2019 - Today

• Data Engineer/ analysis:
o ETL pipelines to follow churn / trial period, generate top , aggregate features for models for all customers, up to 50M lines per day (Python, docker)
o Dashboards analysis for model’s metrics or data analysis in general on Looker

• Data scientist:
o Model for predicting Churn (Tensorflow, keras) (65% accuracy)
o Model for predicting client’s conversion (from trial period to subscribed) (70% accuracy) and around 3-7% improvement in retention.
o Anomaly detection model for royalty’s fraud. (Clustering)
o Persona for clients , every new clients get predicted a “Persona” based on historical clients which is used to calculate a more accurate LTV / ARPU
and understand better what are the clusters of clients we have
(Example : majority of clients are X years old and like Jazz mostly and never download music) ,
currently used by marketing team for better mailing campaign. (Julia MLJ , Clustering)


High Tech

Data Scientist / DevOps / Developer


September 2018 - August 2019

Developed many micro services around data and Machine Learning with Docker / Kubernetes including :
- Machine learning Models (Scikit-learn, TensorFlow) - Report on data analysis.
- Manage databases from different sources (MSSQL, PSSQL) - API (Flask) - mobile app (Android in Kotlin)
- Real time pathfinding algorithm (Derived A* in python3)

AirVisual | The Air Quality Community


Scraper Developer

Beijing City, China

March 2017 - August 2017

Real time data mining from air quality related websites. Scrap data -> Filter -> clean -> add to database Also made minor Forecasting. With MeteorJS and CoffeeScript


Education & E-learning

Lead Developer Chat bot + E-commerce


October 2016 - March 2017

Messenger ChatBot in Ruby on Rails, can converse with a client and create a profile using binary tree questions. E-commerce website

Dipiom Media

Back-end Developer


July 2015 - December 2015

Creation of a website to manage computers in local network. (IP , Hard Drive, copy documents ...) PHP5 , Batch / Shell HTML5 , Materialize Framework (CSS).


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