Research Data Scientist, Principal

Schneider Electric is leading the Digital Transformation of Energy Management and Automation in Homes, Buildings, Data Centers, Infrastructure, and Industries.

With global presence in over 100 countries, Schneider Electric is the indisputable leader in Power Management - Medium Voltage, Low Voltage and Secure Power, and in Automation Systems, providing integrated efficiency solutions, combining energy, automation, and software.

The AI Hub Strategy and Innovation team is looking for experienced technical experts to contribute to the exploration of new technologies and new usages of Machine Learning and Generative Artificial Intelligence.

Missions include:


* Interactions with internal or external customers to gain a good understanding of their needs, propose relevant solutions, and support them as needed.


* Identification and study of emerging technologies.


* Identification, evaluation, and management of innovative partners (e.g., academic partners, startups, ...).


* Definition, execution, and management of relevant innovation projects (e.g., prototype developments, experimentations) to develop and deploy innovations and expertise through research, platforming, standardization, development of intellectual property, partnerships, etc.


* Specification, design, implementation, test, validation, and industrialization of advanced Machine Learning and Generative Artificial Intelligence functions to be incorporated in internal or external products, systems, and solutions.


* Recommendation and management of technical choices (including the selection and management of tool providers and partners) influencing anticipation and offer creation within the AI Hub and beyond.


* Knowledge sharing, teaching, and coaching within the AI Hub and beyond.


* Promotion of Schneider Electric's strategy in the Artificial Intelligence domain through papers, blogs, conference presentations, and contributions to internal and external cross-function communities (sharing with marketing, sales, etc.).

Outcomes include:


* Technology and use case feasibility assessments.


* Patents


* Internal and external presentations, reports, papers.


* Benchmarks, enabling to compare solutions and assess which are practically applicable.

Qualifications:


* Education: A Master or Ph.D.

degree in Computer Science, Artificial Intelligence, Data Science, or a related field.


* Technical Skills: Strong knowledge and 8 to 10 years of hands-on experience with AI technologies, such as Machine Learning, Deep Learning, Natural Language Processing, and Computer Vision.


* Software engineering experience: Capacity to perform coding, debugging, testing, and troubleshooting throughout the application development process and in agile mode.


* Business Acumen: Understanding of industrial applications and business implications of AI technologies, with a focus on driving innovation and delivering tangible results; knowledge of curren...