Renewable energy jobs · Energy Analytics

Energy Analytics Jobs in Renewable Energy

Energy analytics professionals collect, model, and interpret operational and market data from renewable energy assets, transforming raw generation, weather, and grid signals into decisions that improve asset performance and trading profitability. The energy and utility analytics market reached $4.3 billion in 2025, growing at 16.3% annually as operators work to extract value from the data their fleets produce.

What energy analysts actually do

The work splits across two domains. Operational analysts monitor turbine and inverter performance, detect anomalies in SCADA feeds, and build predictive models that flag component degradation before it causes downtime. Commercial analysts forecast generation output, model wholesale electricity prices, and optimise trading strategies for renewable portfolios. The distinction matters: operational analytics requires comfort with time-series sensor data, while commercial analytics demands fluency in energy market structures and pricing mechanisms.

Who hires energy analysts

Most positions sit within asset management teams, independent power producers, or specialised software firms. Power Factors, which manages over 300 GW of wind, solar, and storage assets across 18,000 sites, is the largest dedicated platform in this space and was ranked the #1 energy management system provider by Guidehouse Research in 2025. Other employers on Rejobs include Gridmatic, Volue, Granular Energy, and Octopus Energy - ranging from 11-person startups to utilities with over 10,000 staff.

Roles and titles in demand

Energy Analyst is the most common title, often with a domain suffix: "Renewables and Storage," "Storage & Renewables Trading," or "Energy Market Analyst." Data scientist and data engineer roles appear just as frequently. A single 100 MW solar farm produces several terabytes of sensor data per year - fleet operators managing thousands of sites need people who can turn that volume into actionable intelligence.

At the senior end, directors of energy analytics and trading combine technical modelling with commercial decision-making authority. Product manager roles signal that many analytics employers are software companies building tools for the wider industry, not just running internal teams.

Skills that differentiate

Python dominates, used for everything from forecasting pipelines to data engineering. SQL, time-series databases (InfluxDB, TimescaleDB), and cloud platforms appear in nearly every listing. Machine learning experience - particularly with wind and solar output forecasting - separates senior from mid-level candidates. What distinguishes an energy analyst from a generic data analyst is domain knowledge: wholesale energy trading markets, power purchase agreements, and grid balancing mechanisms.

Where the jobs are concentrated

Boulder, Colorado, and London are the two primary hubs. London's concentration reflects the UK's deep energy trading market and density of asset managers, while Boulder hosts analytics-focused firms including Gridmatic. Glasgow, Brussels, and Athens feature regularly - Athens driven by Southern European solar analytics demand.

What is shifting

The rise of AI for energy applications is compressing the gap between data collection and decision-making. Machine learning pipelines now flag performance anomalies in near-real-time where analysts once spent days building reports. This reshapes rather than eliminates the role: employers want people who can validate and interpret model outputs, not just write queries. UCL and the University of East Anglia both launched dedicated MSc programmes in energy data analytics in 2025-2026, a signal that UK academia sees this demand persisting.