About the Company

A prominent organisation in the energy and utilities sector is advancing its analytics and forecasting capabilities to support the energy transition. The business is committed to leveraging data science and machine learning to optimise grid operations, enable distributed energy resource (DER) integration, and drive innovation in energy management.

About the Role

There are 2 open roles for an 11-month contract opportunity, based in Perth, for a Data Scientist specialising in energy analytics, forecasting, and machine learning.

You will be responsible for developing, validating, and operationalising advanced forecasting models that support grid planning, operations, demand management, and the integration of new energy technologies. The role involves close collaboration with business stakeholders, grid engineers, and data engineers to deliver robust, actionable insights.

Key Responsibilities:

• Develop, test, and deploy machine learning and time-series forecasting models for applications such as load forecasting, DER behaviour, EV charging patterns, solar PV output, and network demand.
• Collaborate with business stakeholders and grid engineers to translate operational needs into data-driven model requirements.
• Work with data engineers to design robust data pipelines, feature stores, and model serving environments.
• Evaluate model performance, develop monitoring frameworks, and tune models for accuracy, stability, and explainability.
• Document model logic, assumptions, and validation results for both technical and non-technical audiences.

The Successful Candidate

You are an experienced Data Scientist or ML Engineer with a strong background in time-series forecasting and energy analytics. You are comfortable working with large, complex datasets and can communicate complex model outputs to business users.

Essential Skills & Experience:

• Proven experience in data science or machine learning engineering.
• Strong hands-on experience with time-series forecasting.
• Advanced proficiency in Python and relevant machine learning libraries.
• Experience working with large energy datasets (e.g., AMI, DER, SCADA, weather).
• Experience building and deploying ML models in cloud environments (Azure ML, Databricks, AWS, GCP).
• Ability to explain complex models to business users and link outputs to operational decisions.
• Experience with Databricks is highly regarded.

Desirable Attributes:

• Experience in energy distribution, grid modelling, DER integration, or utility forecasting.
• Exposure to optimisation algorithms, probabilistic forecasting, and scenario modelling.
• Familiarity with distributed data platforms (SQL, Snowflake, DBT, Databricks).
• Experience supporting operational forecasting in near-real-time environments.

Qualifications:

• Degree in Data Science, Computer Science, Engineering, Mathematics, Electrical Engineering, or a related quantitative field.

What’s on Offer?

• Competitive contract rate (up to $140/hour).
• Opportunity to work on high-impact projects in the energy sector.
• Exposure to advanced analytics, machine learning, and cloud technologies.
• Collaborative and innovative team environment.
• No travel or overtime requirements.