Data Scientist (AI & Machine Learning) – Renewable Energy & Emerging Technologies
London / Hybrid
About the Role
We're looking for an AI-focused Data Scientist to join our Engineering & Development team, helping transform how renewable energy projects are identified, evaluated and developed.
You'll work at the intersection of artificial intelligence, machine learning, geospatial analytics and energy infrastructure, building intelligent models and AI-powered tools that support investment decisions across large-scale Solar PV and Battery Energy Storage System (BESS) projects.
This role goes far beyond reporting and analytics. You'll design predictive models, automate complex engineering workflows, build internal AI applications, and explore how emerging technologies can improve the way renewable energy projects are developed.
You'll also have the opportunity to contribute to new technology areas including data centres, onshore wind and future energy infrastructure.
The organisation sees AI and advanced analytics as a key enabler of future growth and is looking for someone who is naturally curious, enjoys experimenting with new technologies, and wants to build practical AI solutions that deliver real commercial value.
About the Company
Our client is an established and rapidly growing renewable energy developer specialising in the delivery of utility-scale Solar PV and Battery Energy Storage System (BESS) projects across the UK.
Unlike larger corporate developers, the business offers a highly collaborative environment where employees have genuine ownership of their work and the opportunity to influence both technical direction and commercial decisions.
This is an excellent opportunity to join a growing organisation during an exciting phase of expansion, where innovative thinking, continuous learning and the adoption of new technologies are actively encouraged.
Data scientists work closely alongside engineers, planners and commercial teams, developing expertise in renewable energy, power systems and infrastructure while applying modern AI and machine learning techniques to real-world challenges.
Key Responsibilities
- Design and deploy machine learning models to improve site selection, energy yield prediction, revenue forecasting and project optimisation.
- Develop AI-powered internal applications that automate engineering, development and commercial workflows.
- Build intelligent geospatial screening tools using machine learning and GIS datasets to identify and rank development opportunities across the UK.
- Develop predictive models for electricity markets, battery optimisation and project revenues.
- Explore the use of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI copilots and autonomous agents to improve knowledge management and engineering productivity.
- Create scalable data pipelines that ingest, clean and integrate large datasets from weather providers, National Grid, Distribution Network Operators (DNOs), planning authorities and internal systems.
- Build interactive dashboards and decision-support platforms using modern Python frameworks and business intelligence tools.
- Work with engineering teams to apply AI techniques to power systems analysis, curtailment modelling, constraint analysis and renewable energy optimisation.
- Prototype and deploy AI solutions using cloud technologies and modern MLOps practices where appropriate.
- Produce clear visualisations and technical insights for planning applications, investment decisions and stakeholder reporting.
- Continuously evaluate emerging AI technologies and identify opportunities to improve business efficiency through intelligent automation.
Skills & Experience
- Strong Python programming skills with experience using libraries such as Pandas, NumPy, Scikit-learn, XGBoost or LightGBM, and Plotly, Rust, Typescript, Python or Matplotlib.
- Experience developing machine learning models for prediction, optimisation or classification.
- Strong SQL skills and experience working with relational databases.
- Sound understanding of statistics, predictive modelling and machine learning techniques.
- Experience working with geospatial datasets using GeoPandas, QGIS or similar technologies.
- Ability to work with large and complex datasets and build robust data pipelines.
- Excellent analytical and problem-solving skills with the ability to communicate technical concepts clearly to non-technical stakeholders.
- A genuine passion for AI, emerging technologies and continuous learning.