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EV Optimisation Analyst
Employer undisclosedRole managed by a recruiter
Analyze and optimize EV charging network performance using data and forecasting.
Build predictive models to forecast demand growth, charging behavior, and energy costs to support investment decisions and DNO capacity planning.
Analyse tariff structures, grid costs, and energy consumption to optimise site profitability and sustainability.
Work closely with network operations, engineering, fleet, and property teams to align insights with strategic site development and asset optimisation.
Develop new metrics and frameworks for measuring performance, including carbon impact, utilisation per connector, and return on infrastructure investment.
Track utilisation, uptime, session duration, and throughput across the EV charging network using data from charge point management systems (CPMS), telemetry, and CRM tools.
Identify underperforming sites and propose actionable improvements related to energy supply, pricing, location, or equipment configuration.
Develop and maintain data pipelines, dashboards, and automated reports using BI tools (Power BI, Tableau, or Looker) to visualise KPIs for stakeholders across operations, commercial, and engineering teams.
Monitor & Analyse Network Performance:
What you bring
ev charging
real-time data
machine learning
degree
data analyst
problem solving
Ability to translate data insights into actionable business recommendations.
Knowledge of EV charging infrastructure, OZEV grant schemes, or CPMS platforms.
Experience working with large, real-time datasets.
Familiarity with machine learning or predictive analytics for demand forecasting.
Degree in a relevant field (Data Science, Engineering, Economics, or similar).
Proven experience as a Data Analyst, ideally within EV charging, renewable energy, or utilities.
Experience with energy pricing, load balancing, or DNO connection capacity data.
Strong analytical and problem-solving skills with attention to detail.
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