Forecasting Data Scientist

at  SP AusNet

Location:Victoria, Australia
Employment Type: Permanent Full Time

Description:

• Take charge and be responsible for data, AI and analytics projects, ensuring that high-quality forecasts are delivered promptly.
• In a rapidly changing energy landscape act as a trusted liaison for those who use the forecasting process.
• Careers with Purpose > Collaborative > Inclusive > Flexible Work Environment

PURPOSEFUL WORK WITH GENUINELY GOOD PEOPLE. THAT’S REFRESHING.

We are seeking a skilled Forecasting Data Scientist to lead and support various data, forecasting, and analytics projects. Your primary responsibility will be to ensure the timely delivery of high-quality forecasts that are essential for business planning, regulatory compliance, and management purposes.
Success in this role involves developing and maintaining statistical models and capabilities to forecast key demand drivers, such as customer growth and distributed energy resources, while also playing a pivotal role in facilitating communication between various AusNet teams involved in the forecasting process.
With a hybrid split (Office/WFH split) this role is based in Southbank FWP and is part of the Network Strategy & Planning division.

THIS ROLE WILL DELIVER REAL OUTCOMES, INCLUDING BUT NOT LIMITED TO:

Demand forecast: Managing the preparation of projections for major electricity demand drivers, including:

• Customer growth and connections forecasts
• Consumer energy resources (CER) forecasts
• Managing the preparation of minimum and maximum demand forecasts

Data Analysis Leading the development of forecasting data and analytics toolsets

• Work collaboratively with the relevant data, digital and AI teams, to define requirements, develop data, and analytics strategies.
• Working with stakeholders to understanding their needs around demand data, and analytics
• Developing product specifications, technical details and quality requirements
• Contributing to the development of demand forecasting machine learning toolsets
• Regularly meeting with key members of the data, digital and AI teams to discuss the performance of the tools and suggesting improvements and recommend new tools that will result in improved forecasts