Data Scientist

Company

An established renewable energy developer supporting Australia’s energy transition is expanding its analytics capability, combining global expertise with local delivery to develop large-scale clean energy solutions through innovation, data-driven decision-making, and long-term infrastructure investment.

Responsibilities

Forecasting & Modelling

• Build and maintain short-term electricity price and generation forecasting models for the NEM
• Develop battery dispatch optimisation models incorporating energy arbitrage and ancillary services revenue (FCAS)
• Back-test and validate models against live market outcomes, continuously refining performance
• Interrogate NEM behaviour and asset performance data to surface trading opportunities

AI & Machine Learning

• Apply ML and AI techniques to strengthen forecasting accuracy and analytical outputs
• Leverage AI-assisted tooling to accelerate analysis and reporting workflows
• Stay across advances in forecasting and ML, bringing relevant innovations to the team

Data & Infrastructure

• Work with live data pipelines pulling from market operator feeds, SCADA telemetry, and weather data sources
• Maintain data quality standards and ensure model outputs are accurate and delivered reliably to trading systems
• Flag anomalies and market events that may affect model inputs or outputs

Collaboration

• Partner closely with traders to translate commercial questions into modelling problems
• Communicate model outputs, assumptions, and limitations clearly to both technical and non-technical stakeholders
• Contribute to code reviews, documentation, and team knowledge-sharing

About you

Essential

• Proven experience in data science, quantitative analysis, or a related discipline
• Strong grounding in time-series analysis, statistical modelling, and model evaluation
• Demonstrated track record building forecasting or predictive models deployed in production (or near-production) environments
• Proficient Python across the data science stack: pandas, NumPy, scikit-learn, and at least one deep learning framework (PyTorch or TensorFlow)
• Practical experience with AI/LLM tooling in day-to-day analytical work
• SQL proficiency and experience working on cloud data platforms (AWS, Azure, or GCP)

Highly Regarded

• Hands-on experience with electricity market data — particularly NEM dispatch prices, FCAS markets, generation data, and bid/offer stacks
• Familiarity with energy trading concepts: spot markets, ancillary services, battery dispatch, and renewable generation dynamics
• Experience integrating weather-driven or Numerical Weather Prediction (NWP) data into forecasting pipelines
• MLOps exposure: model versioning, monitoring, and automated pipeline deployment

Education

• Degree in a quantitative discipline — Mathematics, Statistics, Computer Science, Engineering, Physics, or Economics
• Postgraduate qualification in data science or ML is a bonus, not a requirement

Next steps

If you have a strong background in data science with strong proficiency in Python and other analytical tools apply now or call Joel on 0466 697 913 for more information.