Data Scientist
Intervene on our customer projects in order to analyze, consolidate and efficiently exploit the data made available, within the framework of a business problem and in an operational context.

Why join Artelys?

Joining Artelys means first of all, joining a dynamic and motivated team, a stimulating work environment and participating in varied and exciting projects, of which here is a small glimpse:

NEXT is a large-scale R&D project of the French Environment and Energy Management Agency (ADEME), which aims to develop an innovative reference software for the dimensioning of flexible electrical grids (smart-grid), thus providing an essential building block for the energy transition. At the heart of the NEXT project is the understanding and modelling of the electricity consumption process on a very fine temporal and spatial scale. Modern clustering techniques make it possible, in particular, to highlight common consumption characteristics. On the other hand, this project is an opportunity to implement and test many predictive modeling techniques, from classical GAM models to modern machine learning techniques and in particular Generative Adversial Networks and Variational AutoEncoders.

Partners: Gaz Electricité Grenoble, INRIA, L2EP

+ infos

On behalf of a major player in the oil sector, we are developing a web application for the restitution and exploration of the results of a complex statistical processing. Based on the Python Dash framework (Flask, Plotly.js, React.js), the application implements, in a very large context, a parsimonious regression technique (linear or not) allowing to select the most impacting variables and restores the results in the form of a dashboard of interactive graphs.

On demand, the execution of the algorithm is transparent for the user who wishes to analyze the results without any prerequisite of understanding the implemented mathematical techniques.


As part of a dynamic, high-level team, you will work jointly on R&D and customer projects, focusing on the analysis and consolidation of data (large and small), the design and implementation of high-performance modeling methods, as well as the visual restitution of these processes.

In particular, you will be brought to:

  • Explore raw data sets (potentially very large and from disparate sources), implement visualization techniques to make sense of them, apply consolidation methods to give them a robust structure as a basis for modeling.
  • Implement and test a wide range of modeling solutions (from classical statistics to modern machine learning techniques), in order to exploit the best combination of them.
  • Develop solutions for visualizing and exploiting results in an operational context



Holder of a Master’s degree and/or PhD with a specialization in the field of data-science and statistics, you have a double competence in mathematics and computer science, especially scientific (R, Matlab, Python).

You are the ideal candidate if:

  • You are curious and approach the search for a new data source like a real game.
  • You master and have implemented clustering, classification and regression methods.
  • You consider that understanding the business context associated with a data problem is essential to its resolution.
  • Driven by a pronounced pragmatism in your modeling choices, you know that the best model is not necessarily the most complicated.
  • You are aware that the world of “Small Data” presents issues and challenges on a par with those of “Big Data”.
  • You are autonomous, rigorous and driven by a strong team spirit.

Without being a mandatory prerequisite, knowledge of Big Data environments and tools (Hadoop, Hive, Spark, MapReduce, Bigtable, NoSQL) is a plus.

In addition, a good fluency in French will be highly appreciated.

Experiencing a strong growth, Artelys is looking for proactive and creative employees, conscious about the added value of their work and motivated to take part in the development of our activities.


Permanent position in our Paris or Lyon office.


This is your dream job? Apply now!


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