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Data Scientist for Industrial performance improvement (H/F)

Position ID : ST-1812-059
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Company :
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Location :
France - Rueil Malmaison
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Axens is an international supplier of technologies, equipment, products and services allowing the transformation of oil, gas, biomass into clean fuels, and the production and purification of major petrochemical intermediates. Its unique range of solutions guarantees optimal performance with a reduced ecological footprint. Axens' global offering is based on highly qualified staff, modern production sites and an extensive global network of industrial, commercial and technical support services.

Axens combines the conviviality of a human-scale company with the reputation of a multinational company with customers in more than 85 countries.

Anchored in the present thanks to a portfolio of hundreds of technologies and high-performance products in constant development, Axens is also future-oriented and prepares the energy transition for its customers with eco-efficient and sustainable solutions 




Axens' customers operate industrial refining and petrochemical processes around the world whose functioning and operation depend on many parameters. Monitoring the performance of these processes makes possible to optimize their performance in order to improve their profitability and reduce their ecological footprint. It is with this in mind that we are gathering industrial data to be able to perform data analytics, to develop new models of process operation and provide our customers with the best advices. For example, through the production of clean fuels, our customers consume a significant amount of energy. Optimization and control of performance reduces energy consumption and contributes to their energy efficiency improvement goals.


The Data Scientist will integrate an innovative, user-friendly and dynamic team working with the Agile method. He/she will work in the Axens Data Lab within the Technology, Development and Innovation team. The Data Lab is a center of expertise in data science serving the Axens Group.


The objective of the position is to define and implement predictive statistical methods on data from industrial refinery processes in order to improve operational performance. A large number of operating parameters (temperatures, pressures, flow rates, etc.) are measured continuously during production and archived in the form of time-series database accessible retrospectively or in real time.



  • Develops and applies time-series-based learning methods (RNN, LSTM, hidden Markov chains) based on existing data


In addition to his/her supervisor, the Data Scientist will be accompanied by technology experts for better understanding of chemical engineering and catalyst manufacturing processes.


Education :
  • Engineer, Masters in Statistics, Mathematics, Computer Science or other quantitative fields
  • Excellent ability to program in Python or R.
  • Knowledge of SQL and NoSQL databases.
  • Basic knowledge of process engineering is a plus in order to make sense of the data analysis you perform.
  • Fluent English is mandatory
  • You have real basis in machine learning and more specifically in descriptive statistics and the construction of predictive statistical models based on real-world data in a production environment. You have excellent analysis and coordination skills and you know how to work in a team using the Agile method.
  • Being curious, you do not hesitate to document and stay abreast of innovations and nurture your creativity with information that you know how to fetch for yourself.

6 months internship – Beginning in march / april

Apply now