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Ngôn ngữ:

Data Scientist F/M

Vị trí:
GRENOBLE, France
(Các) Thể loại:
Information Technology
ID Req:
006OI5

Mô tả Công việc

Schneider Electric is leading the digital transformation of energy management and automation in homes, buildings, data centers, infrastructure, and industries. With a global presence in more than 100 countries, Schneider Electric is the undisputed leader in energy management - medium-voltage, low-voltage and secure power, and automation systems, providing integrated efficiency solutions that combine energy, automation and software.

Our long-standing strategy at Schneider Electric is to consider environmental, social, and governance issues in every aspect of our business, while helping our customers and business partners achieve their own sustainability goals. We are honored to be ranked as the world's most sustainable company in 2021 by the Corporate Knights Global 100 Index. This ranking underscores the company's transformation as a leading provider of digital solutions that facilitate energy efficiency and sustainability.  

In order to remain a major player in this transformation, Schneider Electric's Global Supply Chain Europe department is strengthening its Intelligent and Advanced Digital Solutions teams.

Would you like to be part of this exciting adventure? Are you ready to share your skills and data knowledge with us?

If you are a problem solver using data as a primary source of truth, a person interested in solutions to predict actions to be taken on the basis of data, and you want to be part of a brand new team whose mission is to take all European Global Supply Chain teams to the next level, then you are potentially our future collaborator!

We are looking for a passionate ML/IA engineer with a proven ability to generate results by leveraging AI, Machine Learning and Deep Learning techniques. As such, you will have the opportunity to work with a wide range of stakeholders and teams, helping them to solve industrial or logistical problems and thus enable them to be more efficient.

Your missions :

  • Analysis (use case, AI, data science, set of corresponding data...) ;
  • Specification, design, implementation, testing, validation and industrialization of advanced data management, artificial intelligence and analytical functions in order to develop an autonomous process ;
  • Contributing to technology watch (scientific literature, patents, trend analysis, business assessment) and experimentation of new technologies, new tools and processes, in order to improve products and services as well as development practices within the company ;
  • Contribution to the identification and evaluation of potential external partners ;
  • Sharing knowledge and training with the community

Qualifications

Qualifications
- Ideally, you have two years of experience in data processing, analysis, AI and/or data science model development.
- Master's, PhD or equivalent degree in the following fields: 
     Analytics, Artificial Intelligence, Data science or related field
- Software engineering skills/experience: Ability to perform coding, debugging, testing (including unit testing, functional testing and integration testing), troubleshooting throughout the application development process and in agile mode.
- Experience with major machine learning frameworks such as Pytorch, Scikit-Learn, Tensorflow, Pandas, SparkML, etc.
- Mastery of programming, via Python, R or other equivalent languages
- Very good knowledge of vector algebra, statistical and probabilistic modelling
- Good knowledge of databases such as MySQL, Oracle, SQL Server, NoSQL, etc.
- Ease of communication, especially for data storytelling: ability to convince 
- Autonomy & ability to cooperate.
- Open-mindedness & scientific rigour.
- Fluent English.


The little extras that will make the difference :
- Knowledge of exploratory data analysis and hypothesis testing to identify opportunities for Machine Leraning and Deep Learning.
- Experience working with Amazon SageMaker or Azure ML Studio for deployments 


Schedule: Full-time
Req: 006OI5
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