Support the development of the tools and effective data management used to analyze the performance of operating assets in the Americas region (onshore wind, solar, and battery storage), including visualizations, data blending, and data validations
Support the design and implementation of indices, key metrics, and data models to identify performance improvement opportunities
Develop the existing data platform to facilitate analysis with focus on anomaly detections as well as monitoring the performance of assets
Build high quality pipelines to collect, load, clean, and transform large datasets
Validate reporting provided by suppliers for adherence to contract requirements
Develop, report, and manage the implementation of new metrics, algorithms, and indicators for operating assets
Test and implement data sources used for analysis and reporting, including availability and quality assessments of data
Refine and optimize processes in relation to internal and external reporting deliverables
Collaborate with internal stakeholders to shape organizational views and decisions
Promote and support analytics improvements within the renewable industry by exchanging technical expertise, real-world challenges, and cutting-edge methodology with other industry professionals

Master’s degree (or foreign equivalent) in industrial engineering, computer science, mathematics, or related field; plus 1 year (12 months) of experience in job offered or similar occupation in the energy industry
Bachelor’s degree and 3 years (36 months) of experience is acceptable in the alternative
Knowledge of renewable energy sector (wind, solar, storage, electricity markets, incentives, and regulatory framework)
NERC compliance
Statistical and machine learning models
OEM software
Data modeling and performance analysis (input variable, back-end data structures, front-end reporting dashboards)
Monitoring asset performance (lost energy, curtailment impacts, turbine availability, and other KPIs for asset optimization)
ETL pipelines (SCADA data and meter data)
Experience in BI dashboards (Power BI or Tableau)
SQL databases (SQL queries, stored procedures, views, functions, etc.)
Python (Pandas, NumPy, Matplotlib, GGplot, Scikit-learn, etc.)
Version control tools (Git)
Azure
Working in an Agile environment

Senior Analyst, Asset Performance

Key skills