Data Scientist

Remobi; France; À distance; EUR 50 000 - 70 000; Temps partiel

Résumé du poste

A technology solutions company is seeking a Remote Data Scientist to optimize energy grid control using Reinforcement Learning models. This role requires expertise in Python and AWS services, along with experience in grid simulation tools. Candidates should hold a degree in a related technical field and be passionate about sustainability and AI. This is a contract position for an initial duration of 12 months.

Qualifications

• Proven experience with Reinforcement Learning, ideally applied to physical or control systems.
• Advanced Python programming and model deployment skills.
• Hands-on use of tools like Grid2Op, L2RPN, ICTE, or similar simulation environments.

Responsabilités

• Design, train, and deploy RL models to optimize real-time grid operations.
• Use open-source grid simulation platforms to develop and validate models.
• Ensure models comply with regulatory and sustainability standards.

Connaissances

Reinforcement Learning

Python programming

Model deployment

AWS services

Grid simulation tools

Formation

Degree in Computer Science

Outils

Grid2Op

L2RPN

ICTE

Description du poste

We are Remobi – we empower businesses to scale, innovate, and achieve their goals through high-quality technical solutions delivered by high-performing, high-quality, REMOTE nearshore technology teams.

Position Overview:

Location: Fully Remote

Role Type: Freelance/B2B/Contract

Duration: Initial 12 Months

Position Summary:

We’re hiring a Data Scientist to build and deploy reinforcement learning (RL) models that optimize real-time control of energy grid systems. This role focuses on developing scalable, responsible AI solutions that reduce emissions, support compliance, and improve operational efficiency. You’ll work with cutting-edge tools like Grid2Op, L2RPN, and ICTE, integrating your work into cloud-native environments with Python and AWS.

This position suits someone passionate about sustainability, operational AI, and solving complex, real-world challenges.

Responsibilities:

• Design, train, and deploy RL models to optimize real-time grid operations.
• Use open-source grid simulation platforms (Grid2Op, L2RPN, ICTE) to develop and validate models.
• Ensure models comply with regulatory and sustainability standards for AI systems.
• Deploy and scale models using AWS services such as SageMaker, Lambda, and S3.
• Collaborate with engineers, compliance teams, and energy operations specialists.
• Translate technical insights into clear communications for varied stakeholders.

Qualifications:

• Proven experience with Reinforcement Learning, ideally applied to physical or control systems.
• Advanced Python programming and model deployment skills.
• Hands-on use of tools like Grid2Op, L2RPN, ICTE, or similar simulation environments.
• Experience deploying models on AWS (SageMaker, Lambda, S3).
• Familiarity with smart grid technologies or energy systems is a plus.
• Understanding of AI governance, sustainability metrics, or regulatory frameworks.
• Degree in Computer Science, Engineering, Applied Mathematics, or related technical discipline.

We are an equal opportunities employer and welcome applications from all qualified candidates.