Job description
Join a fast-growing renewable energy company focused on solar, wind, and storage projects. As a Renewable Energy Data Analyst based in Austin, TX, you will leverage data science to optimize project performance, forecast generation, and support strategic decisions across our portfolio.
In this role you will collaborate with engineering, finance, and operations teams to turn data into actionable insights that accelerate project timelines and improve asset ROI. We offer competitive compensation, generous benefits, and a vibrant, mission-driven culture committed to sustainable energy transition.
Responsibility
- Collect, clean, and analyze project performance, financial, and operational data across solar, wind, and storage assets.
- Build dashboards and KPIs to monitor project economics, capacity factors, and asset utilization.
- Develop forecasting models for energy generation, market prices, and risk scenarios under different grid and policy conditions.
- Collaborate with engineering, procurement, and site operations to identify optimization opportunities and support asset interconnection processes.
- Generate data-driven recommendations for resource planning, maintenance scheduling, and capital allocation.
- Ensure data governance, quality, and reproducibility; document workflows and pipelines for cross-functional teams.
- Communicate insights effectively to executives and non-technical stakeholders through clear visuals and storytelling.
Qualification
- Bachelor’s degree in Data Science, Electrical Engineering, Physics, or related field; Master’s preferred.
- 3+ years of hands-on data analysis experience in renewable energy or power sectors.
- Proficiency in Python (pandas, numpy) and SQL; experience with R is a plus.
- Strong data visualization skills (Tableau or Power BI) and familiarity with GIS concepts.
- Solid understanding of energy markets, project economics, and incentives.
- Experience with asset-level data (SCADA, SCADA-like systems) and data pipelines; familiarity with data governance.
- Excellent communication and collaboration skills; ability to present complex findings to technical and non-technical audiences.