About the Role
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.
Key Responsibilities
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.
Mandatory Professional & Technical Requirements
* 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
.
Desirable Skills & Attributes
* 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 or email: 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.