Job Title:
Data Scientist: Enterprise & Asset Performance
Location:
Melbourne (Hybrid)
Employment Type:
Full-time
Salary:
$90,000
About the Role
We are seeking a Data Scientist: Enterprise & Asset Performance, to join our growing AI and analytics consultancy, focused on energy, resources, utilities and asset-intensive industries.
This role sits at the intersection of energy engineering, consulting and applied data science, supporting the delivery of AI-driven optimisation, analytics and decision-support solutions for enterprise clients.
Key Responsibilities
* Apply energy engineering expertise to real-world optimisation and analytics challenges across energy, utilities and industrial environments
* Design, develop, and deploy data science and machine learning models to support asset performance, operational efficiency and predictive insights
* Build and maintain data pipelines and data engineering frameworks to support production-ready analytics solutions
* Support consulting engagements, including problem definition, analysis, client presentations and delivery support
* Work closely with senior stakeholders, technology partners and internal teams across multiple concurrent projects
* Contribute to the development of reusable analytics frameworks and consulting methodologies
* Lead end-to-end delivery of data science and ML projects, from requirements discovery and problem framing through to deployment, production integration and post-implementation monitoring
* Design and implement automated data workflows and reporting pipelines, including performance dashboards and analytical views across multiple business dimensions (operational, commercial, financial)
* Work collaboratively with data/ML engineers and solution architects to embed models and analytical components into cloud platforms and client systems, ensuring robustness, scalability and production readiness
* Develop data dashboards, present analytical findings and explain model behaviour to technical and non-technical stakeholders
* Communicate clear recommendations that support data-driven decision-making at operational, commercial and executive levels
* Design and configure agentic AI solutions, including defining agent roles, setting up and maintaining knowledge bases for agent context and implementing analytics to monitor and optimise agent performance and outcomes
* Design and run Python/SQL-based data workflows that support recurring reporting, dashboards and decision-support tools in production environments
Required Skills & Experience
* Bachelor's Degree in Energy Engineering, Data Science, Statistics, Analytics (or closely related discipline)
* Experience in management or technical consulting (ideally within energy, utilities, or industrial sectors)
* Strong applied data science skills (Python, machine learning, analytics)
* Experience with PySpark, XGBoost/LightGBM and frameworks like TensorFlow/Keras or PyTorch
* Strong SQL skills for large, complex datasets
* Specific cloud platform experience (Azure Databricks, AWS Lambda, S3, etc.)
* Experience with time-series forecasting, statistical modelling, classification, regression and clustering
* Familiarity with BI tools (Power BI, Tableau)
* Data engineering capability, including data integration and pipeline development
* Ability to operate across both technical delivery and client-facing consulting environments
Desirable Experience
* Background in energy, utilities, oil & gas, or asset-intensive industries
* Experience working with enterprise clients or large consulting firms
* Exposure to AI-driven optimisation, asset performance, or industrial analytics
Why Join Us
* Work on real-world, high-impact AI and energy projects
* Join a fast-growing consultancy with strong global partners
* Opportunity to shape both technical solutions and consulting capability
* Exposure to enterprise-scale clients across multiple industries