Research & Innovation Manager; Automation

Want to help the world move towards Net Zero and shape the future of energy from within the UK’s leading energy providers?

Energised Futures is Centrica's in-house science, research and innovation incubator, established to systematically explore the possible and catalyse Centrica’s purpose of energising a greener, fairer future. To do this, we’ve built a dynamic and diverse team of researchers to perform cutting edge innovation across its core themes of flexibility, automation, connectivity, markets, engagement, and access, and pairing this with a strong support team to publish and promote research activities, engage with other research institutions and energy innovators, and grow our portfolio of activities.

Based in Antwerp and London since 2024, we continue to grow and evolve, giving newcomers to the team the chance to play a pivotal role in shaping the team and its processes, as it in turn shapes the roadmap for the wider organisation and industry.

Our Research and Innovation Managers lead and mentor teams of research professionals, oversee highly technical projects, and own the strategy and roadmap for their area, ensuring alignment with the company's strategic objectives. The Automation theme covers all methods and technology that bring digitisation and optimisation of energy to scale using complex algorithms based on data science, machine learning, and the full spectrum of AI techniques (e.g. generative, agentic, etc).

Specifically, the role entails:

• Leading and developing a team of research engineers
• Ensuring reliable delivery of high-quality research and innovation outputs
• Owning the Energised Futures’ strategy around the automation pillar
• Collaborating and engaging with stakeholders, both across Centrica, the energy industry, startups and academia
• Supporting the wider business to adopt and deploy our outputs to maximise our impact
• Monitor and engage with industry and academia by engaging with conferences and journals

The team is currently based in Antwerp, Belgium but we will be building a London-centred team to match. It will be useful to be able to travel between the locations, but we’d prefer you to be based in or around London.

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.

Of course, we’re also adaptable – if you think you’d be a good fit but don’t have all of this then we’d still love to hear from you!

• 5+ years experience designing complex statistical algorithms or machine learning models: A PhD plus 2 or more years or a master’s degree plus 4 or more years of research or equivalent industry experience in a domain such as Computer Science, Electrical Engineering, Control Systems, or a related field
• Experience across a spectrum of libraries, frameworks and services
  : such as ML libraries e.g. Tensor Flow or PyTorch; model servers such as AWS Bedrock; MLOps such as ML Flow or Sagemaker; agent / AI orchestration such as Lang Graph or MCP libraries
• Strong programming skills, especially in Python (other languages like C++, Scala, Rust etc are bonuses). Practical experience implementing and deploying using various techniques including for (deep) supervised / unsupervised / reinforcement learning problems
• Strong mathematical skills and analytical mindeset
• Energy industry knowledge is strongly preferred e.g. smart energy technologies and energy management, and connectivity challenges, energy markets and trading techniques, regulatory constraints and processes, etc

• An adaptable growth mindset: Curiosity and a desire to learn and develop beyond current expertise. Proactive, creative, and collaborative approach to problem-solving, especially in the ambiguous, uncertain world of innovation
• Strong sense of ownership: taking initiative and being accountable for your work and the wider team
• Interpersonal skills: working effectively with in cross-functional teams
• Technical communication: e.g. in discussing and explaining technical concepts such as machine learning, energy systems, hardware control,…