Senior Data Scientist

Location: Australia | Sydney preferred |

Full-Time A rapidly growing energy technology group is seeking a Senior Data Scientist to lead the development of forecasting and optimisation models across distributed energy systems. This role sits at the intersection of data, engineering, and climate impact—ideal for someone passionate about applying machine learning to real-world infrastructure. You’ll work with high-frequency time-series data to improve solar and battery performance forecasting, market pricing models, and system orchestration. The position offers hands-on collaboration with software engineers, product teams, and energy specialists in a fast-paced, high-trust environment.

Key Responsibilities:

• Design and deploy ML models for solar output, energy demand, and battery behaviour

• Build predictive tools for system control, dispatch scheduling, and VPP responsiveness

• Analyse telemetry data from solar, battery, and metering devices to extract insights

• Develop market pricing models using historical and live grid data

• Collaborate cross-functionally to translate complex questions into data-driven solutions

• Monitor data quality and build anomaly detection pipelines to ensure platform reliability

• Support modelling of energy savings, operational efficiency, and market participation What

You’ll Bring:

• 3–6 years’ experience in data science, ideally working with energy/renewable energy

• Strong Python and SQL skills (pandas, scikit-learn, NumPy, etc.)

• Experience with time-series datasets and forecasting models

• Familiarity with cloud-native data tooling (GCP preferred)

• Ability to work iteratively and thrive in ambiguity

• Must be based in Australia; Sydney-based candidates preferred

This is a unique opportunity to join a mission-driven team building the next generation of energy intelligence.