Adam Wybierala

Machine learning engineer

Moves to Créteil, Paris

  • 48.7779
  • 2.45319
  • Indicative rate €350 / day
  • Experience 2-7 years
Propose a project The project will only begin when you accept Adam's quote.

Confirmed availability

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

Location and geographical scope

Créteil, France
Can work in your office at
  • Créteil and 50km around
  • Paris and 20km around


Project length
  • ≤ 1 week
  • ≤ 1 month
  • Between 1-3 months
  • Between 3-6 months
  • ≥ 6 months
Business sector
Would prefer avoiding:
Banking & Insurance
Company size
  • 1 person
  • 2 - 10 people
  • 11 - 49 people
  • 50 - 249 people
  • 250 - 999 people
+2 autres




  • Français

    Native or bilingual

  • Anglais

    Native or bilingual

Skills (7)

  • Shell
  • Beginner Intermediate Advanced
  • Version Control
  • Git
    Beginner Intermediate Advanced
  • All
  • Beginner Intermediate Advanced

Adam in a few words

Bonjour :)

Je suis un développeur de l’École 42 ayant suivi de nombreuses formations en machine learning et data science et je n’arrête jamais d'apprendre ! Je travaille principalement en Python, et je peux intervenir sur des projets de Data Science, Machine Learning, Back end ou développement Python.



Food Industry

Data Scientist

Moussy-le-Vieux, France

April 2019 - December 2019

I set up a Raspberry Pi with a camera to detect objects with Machine Learning.
Used ETL to extricate data from Excel spreadsheets to determine the most energy consuming part of the sugar extraction process.
I created a simple decision assistant algorithm after data exploration and understanding of a critical part of the process.



Data Scientist

Paris, France

September 2016 - March 2018

I mainly worked on scripts and software to automatize important tasks that were not done due to lack of time and people. I developped and maintain software in Python to create entities on ads platform resulting in a huge improvement in organizational efficiency and effectiveness, and developped deployed and maintained Python script to allocate budget between entities at any level based on performances and constraints.



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