Data Scientist

Role Overview

We're seeking a highly analytical and commercially minded Data Scientist to join a Melbourne-based energy trading team and contribute directly to the models that support decision-making across a growing portfolio of battery, wind, and solar assets.

In this role, you'll develop and maintain forecasting models, analyse live NEM market data, and leverage AI and machine learning tools to improve trading and operational performance. This opportunity is well suited to someone with strong forecasting and quantitative modelling capabilities who is looking to further develop their expertise within Australia's evolving energy markets.

Working closely alongside experienced traders in a fast-paced office environment, you'll gain direct exposure to live market activity and see how your analytical work influences real commercial outcomes. Your contributions will play a key role in improving trading strategies, forecasting accuracy, and revenue performance across the portfolio.
About the Company

Our client is a major renewable energy platform with a significant and rapidly expanding presence across Australia's clean energy sector. The business owns and operates a large portfolio of utility-scale battery energy storage systems (BESS), alongside wind and renewable generation assets across the National Electricity Market (NEM).

With multiple large-scale projects under development and operation across Victoria, New South Wales, Queensland, South Australia, and Tasmania, the company is playing a key role in supporting Australia's energy transition. Backed by international investment and an experienced leadership team, the organisation continues to scale its portfolio and trading capabilities across the region.

Skills & Experience Essential

• Experience in data science, quantitative analytics, forecasting, or a related technical discipline
• Strong understanding of time-series analysis, statistical modelling, and model validation techniques
• Demonstrated experience building predictive or forecasting models and deploying them into production or operational environments
• Strong Python capability across libraries such as pandas, NumPy, scikit-learn, and at least one deep learning framework (PyTorch or TensorFlow)
• Experience using AI-assisted tools and modern machine learning workflows
• Proficiency in SQL and experience working with cloud-based data platforms such as AWS, Azure, or GCP

Desirable

• Exposure to electricity market data, particularly AEMO NEM datasets including pricing, FCAS, generation, and bidding data
• Understanding of energy trading concepts including spot markets, ancillary services, battery optimisation, and renewable generation
• Experience integrating weather datasets or Numerical Weather Prediction (NWP) data into forecasting workflows
• Familiarity with MLOps practices including model monitoring, version control, and automated deployment pipelines

Education

• Bachelor's degree or higher in a quantitative discipline such as Mathematics, Statistics, Computer Science, Engineering, Physics, or Economics
• Postgraduate qualifications in Data Science, Machine Learning, or a related field are advantageous but not essential

Key Competencies

• Strong analytical capability with a structured and methodical approach to modelling and validation
• Commercial mindset with the ability to link analytical outputs to trading performance and business outcomes
• Curious and proactive approach to problem-solving and continuous improvement
• Strong communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders
• Collaborative team player who thrives in an office-based, fast-paced trading environment

Key Responsibilities Analytics, Forecasting & Modelling

• Analyse NEM market behaviour and asset performance to identify trading and optimisation opportunities
• Develop short-term electricity price and generation forecasting models
• Support battery optimisation and dispatch modelling across energy and FCAS markets
• Back-test and refine models using live market outcomes and operational data

AI & Machine Learning

• Apply machine learning and AI techniques to improve forecasting, analytics, and trading performance
• Utilise AI-assisted tools to streamline analysis and reporting workflows
• Stay across emerging developments in forecasting and AI/ML technologies and contribute new ideas to the team

Data & Systems

• Work with data pipelines ingesting market, operational, SCADA, and weather data
• Ensure forecasting outputs are accurate, reliable, and delivered to trading systems in a timely manner
• Monitor data quality and investigate anomalies or market events impacting model performance

Collaboration

• Partner closely with traders and commercial stakeholders to translate business challenges into analytical solutions
• Clearly communicate modelling assumptions, outputs, and limitations
• Contribute to knowledge sharing, documentation, and code review processes within the team

What's on Offer

• Competitive salary package plus performance-based bonus
• Opportunity to work directly alongside experienced energy traders in a live market environment
• Strong learning and development opportunities within a high-growth renewable energy business
• Exposure to large-scale battery storage, renewable generation, and energy trading operations across the NEM
• Modern cloud-based technology environment with contemporary tools and systems
• Clear long-term growth opportunities as the trading and analytics function continues to expand