Missions :

• Analyze and understand large volumes of data in various fields (rental, logistics, retail, logistics, shipping) in order to identify all revenue optimization levers,
• Think and design the optimization engines needed to activate these levers,
• Build, test, and deploy the necessary predictive models (time series prediction, segmentation, etc.),
• Format results in a clear and concise manner.

Our technical stack :

• Backend : Python, Redis, Prostgre, SQL, Celery,
• Frontend : React JS, Redux.js,
• DevOps : Terraform, Sagemaker, Kubernetes, GitHub, Docker, AWS lambda, AWS,
• Data : Tableau, Snowflake, Scikit-learn, Python (Data Science), Mixpanel, Kuberflow, Dataiku, Apache Spark

You have excellent qualifications in mathematics and statistics, a strong taste for business issues, as well as a first experience (or personal projects) with Python and the usual Machine Learning algorithms.

• You have an excellent knowledge of Pandas, Scikit-Learn and SQL,
• You know how to use and explain the main ML algorithms,
• You are autonomous, able to make decisions,
• You are able to solve complex problems,
• You have a perfect command of English,
• Mastery of Tableau Software, Dataiku, or AWS are pluses.

• Phone interview with Thomas (Data Engineer & Data Scientist)
• Technical Test
• Phone interview with Nicolas (Head of Data Projects)
• HR interview with Erell