PERFORMANCE OPTIMISATION ENGINEER (F/M/D) BESS | IGNITIS RENEWABLES
Core
Apply advanced analytics and machine learning to optimize the performance of renewable energy assets, specifically Battery Energy Storage Systems (BESS), by conducting performance verification, health analysis, and fault prediction.
Role type
Performance Optimization Engineer (Data Science & Engineering)
Builds
Machine learning models for performance forecasting, asset deterioration, condition monitoring, and fault prediction; business cases for asset upgrades.
Domain
Renewable Energy / Battery Energy Storage Systems (BESS) / Operations & Maintenance
Deliverable
production ML models | dashboards & analysis | client delivery
Required skills
Machine learning model development, advanced statistical methods, data analysis for large-scale datasets, asset upgrade viability assessment, data visualization (Power BI), root cause analysis, technical fault code interpretation
Preferred skills
Renewable energy sector experience, engineering background in physics or related fields, ability to explain technical insights to non-technical stakeholders
Technologies
Power BI, MS Office, Machine Learning frameworks
Responsibilities
Conduct regular and ad-hoc analysis on performance verification and component health; Develop, run, and improve machine learning models for forecasting and condition monitoring; Identify areas for performance improvement across the portfolio; Support investigations into lost production events and fault analysis; Advise asset supervisors on technical issues and performance concerns.
Seniority
Junior to Mid-level, hands-on IC