Research & Innovation: Automation - Data Science

This hybrid managerial role, based in Windsor, Berkshire (2 days on-site), offers an exciting opportunity to shape strategy and processes while driving innovation in the energy industry. We are looking for an adaptable, experienced data scientist or machine learning expert that wants to tackle complex challenges and push the state of the art for automation in the energy sector.

If you're passionate about innovation and making an impact, apply now!

Key responsibilities will include:

• You will lead and mentor research teams, oversee technical projects, and own the strategy and roadmap for the Automation theme, focusing on digitizing and optimizing energy at scale using advanced data science and machine learning techniques.

• As part of a dynamic team, you'll work across key themes like flexibility, automation, and connectivity, supported by a group dedicated to promoting research and fostering collaborations.

Here's what we're looking for:

Strategic Leadership:

• Lead and mentor a team of Research Engineers, fostering collaboration and supporting professional development.

• Drive high-quality research by planning and executing innovative projects, developing novel algorithms, and integrating data science and machine learning techniques.

• Create and implement research strategies aligned with company objectives, staying ahead of industry trends to identify new opportunities.

Collaborative Spirit:

• Partner with internal teams and external stakeholders, including academia and industry, to enhance innovation and research outcomes.

• Translate research findings into practical applications, working with stakeholders to streamline the commercial handover process.

• Promote continuous learning, publish findings in journals, and represent the team at conferences, producing impactful reports and insights.

Technical Excellence:

• Advanced degree in Computer Science, Electrical Engineering, Control Systems, or related field

• Practical experience designing statistical optimisation algorithms and (deep) machine learning techniques.

• Proficiency in machine learning frameworks like TensorFlow, PyTorch, scikit-learn, or XGBoost.

• Proficient in Python; knowledge of Scala, C++, Go, Rust, or Julia is a plus.

• Experience with git-based workflows and collaborative software development.

• Ability to write clean, efficient, and maintainable code.