Data Scientist / Engineer (H/F)

  • Par Generationnel
  • CDI
  • Paris (Paris)
  • Master, Bac +5
2016-10-12T23:45:56+0200

Description de l'offre

The Data Engineer/Scientist is in charge of designing and implementing the
predictive algorithms for the optimal energy management of the control system.
He will be in charge of developing the forecasting models for the following:
electricity consumption, Solar production forecast…
You will be:
- You will develop online learning methods for load & solar forecasts
- Involved in the product features strategy & decisions you will have a direct impact on the company
- At the heart of our core technology and value proposition
- Test the algorithms through the whole control software pipeline to select the best methods to be used
In the Energy analysis & forecasts team you will:
- Choose and implement artificial intelligence algorithms
- Perform efficiency tests on our datasets
- Test Robustness & scalability test on our micro-grid pilot project


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Pour postuler :
http://generationnel.contactrh.com/jobs/4529/15762568

Profil recherché

Masters in electrical engineering, computer engineering, computer science or
related fields
(statistics, applied mathematics).
- One or more year of artificial intelligence and machine learning algorithms experience
- Neural Networks Frameworks
- One or more year of Python or R programming experience
- Machine learning libraries
- Statistical models
BONUS QUALIFICATIONS
- PhD in electrical engineering, computer engineering, computer science or related fields
- Knowledge in Amazon Web Services Frameworks: Kinesis, EC2, S3, Firehose
AND NEXT ? – BE PART OF THE ADVENTURE
We are constantly searching for the brightest minds to help us build
tomorrow's energy grid, if you
enjoy working with us we will be happy to get you on board of this great
adventure!

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À propos de Generationnel

Elum Energy is a software as a service company developing the Energy Operating System (Energy OS), an energy management software for solar panels coupled with batteries installed in industrial and commercial buildings. We leverage the power of learning algorithms to store the solar power and deliver it when needed the most. Our technology allows to lower the electricity bill, ensures a reliable renewable energy supply and participates in the grid stability.

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