Thursday, May 01, 2014

CSJob: Data Scientist Position. Chaire "Economie et gestion des nouvelles données"

Gabriel Peyre sent me the following three weeks ago but it slipped through the many things that happened this past month:

Dear Igor,

If you think it is interesting for your readership, would it be possible that you post some advertisement for the following position ?

All the best


Here is the announcement:

Position as data scientist
Chaire "Economie et gestion des nouvelles données"

  • Location: within one of the lab of the chaire (Paris-Dauphine, ENS Ulm, Ecole Polytechnique or ENSAE).
  • Duration: 1 year renewable at least once.
  • Salary: to be discussed depending on the applicant’s profile.
  • Start: as early as May 2014, and no later than September 2014.
  • Application process: send a resume and a motivation letter to:
    Stephane Gaiffas <>
    Robin Ryder <>
    Gabriel Peyré <>

Job description

The chaire "Economie et gestion des nouvelles données" is recruiting a talented young engineer specialized in large scale computing and data processing. The targeted applications include machine learning, imaging sciences and finance. This is a unique opportunity to join a newly created research group between the best Parisian labs in applied mathematics and computer science (Paris-Dauphine, ENS Ulm, Ecole Polytechnique and ENSAE) working hand in hand with major industrial companies (Havas, BNP Paribas, Warner Bros.). The proposed position consists in helping researchers of the group to develop and implement large-scale data processing methods, and applying these methods on real-life problems in collaboration with the industrial partners.

A non-exhaustive list of methods that are currently investigated by researchers of the group, and that will play a key role in the computational framework developed by the recruited engineer, includes :
  • Large scale non-smooth optimization methods (proximal schemes, interior points, optimization on manifolds).
  • Machine learning problems (kernelized methods, Lasso, collaborative filtering, deep learning, learning for graphs, learning for time-dependent systems), with a particular focus on large-scale problems and stochastic methods.
  • Imaging problems (compressed sensing, super-resolution).
  • Approximate Bayesian Computation (ABC) methods.
  • Particle and Sequential Monte Carlo methods

Candidate profile

The candidate should have a very good background in computer science with various programming environments (e.g. Matlab, Python, C++) and knowledge of high performance computing methods (e.g. GPU, parallelization, cloud computing). He/she should adhere to the open source philosophy and possibly be able to interact with the relevant communities (e.g. scikitlearn initiative). Typical curriculum includes engineering school or Master studies in computer science / applied maths / physics, and possibly a PhD (not required).

Working environment

The recruited engineer will work within one of the labs of the chaire. He will benefit from a very stimulating working environment and all required computing resources. He will work in close interaction with the 4 research labs of the chaire, and will also have regular meetings with the industrial partners. More information about the chaire can be found online at

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