We are seeking an experienced Data Scientist with deep expertise in machine learning, time-series forecasting, and energy analytics. You will play a key role in developing and operationalising advanced forecasting models that support grid planning, network operations, DER integration, demand management, and the broader energy transition.

This is an opportunity to work on complex, high-impact modelling challenges that directly shape the future of the energy sector.

You will be responsible for performing the following tasks on a daily basis:

• Design, develop, test, and deploy ML and time-series forecasting models for load forecasting, DER behaviour, solar PV generation, EV charging patterns, and overall network demand.

• Collaborate closely with business stakeholders, grid engineers, and operational teams to translate forecasting needs into robust analytical and model requirements.

• Work with data engineers to design and optimise data pipelines, feature stores, and model-serving environments.

• Evaluate and tune models for accuracy, stability, and explainability; build monitoring and alerting frameworks for production models.

• Document model design, assumptions, validation results, and deployment practices for both technical and non-technical audiences.
  
  

• 5+ years of experience in Data Science or Machine Learning engineering roles.

• Strong hands-on experience with time-series forecasting and predictive modelling.

• Expertise in Python and ML/AI libraries (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, Prophet, etc.).

• Experience working in Databricks (preferred).

• Demonstrated ability to work with large and complex energy datasets (AMI, DER, SCADA, weather, etc.).

• Ability to explain complex model outputs to business users and connect insights to operational decision-making.

• Experience deploying ML models in cloud environments such as Azure ML, Databricks, AWS, or GCP.
  
  

• Background in energy distribution, grid modelling, utility forecasting, or DER integration.

• Exposure to optimisation algorithms, probabilistic forecasting, and scenario modelling.

• Familiarity with distributed data platforms (SQL, Snowflake, DBT, Databricks).

• Experience supporting near-real-time operational forecasting environments.
  

To be considered for the role click the 'apply' button or for more information about this and other opportunities please contact Yash Kumar Jain on 03 8680 4235 or email: [email protected] and quote the above job reference number.

Paxus values diversity and welcomes applications from Indigenous Australians, people from diverse cultural and linguistic backgrounds and people living with a disability. If you require an adjustment to the recruitment process, including the application form in an alternate format, please contact me on the above contact details.