​Data Scientist (AI & Machine Learning) – Renewable Energy & Emerging Technologies

Overview

In this role you will design and deploy AI-driven models to optimize site selection, yield, and revenue for large-scale solar and BESS projects. You’ll work with geospatial data and energy infrastructure to deliver practical AI tools that support investment decisions and project development. You’ll explore emerging tech like LLMs and RAG to boost knowledge management and engineering productivity, while collaborating with engineers, planners, and commercial teams. This position offers the chance to shape AI-enabled processes across renewable energy domains and evolving tech areas.

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

Key requirements

• Strong Python programming skills with 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

• Analytical thinking
• Clear communication
• Curiosity and learning mindset
• Python
• Pandas
• NumPy

…