Energy Asset Optimisation Specialist — Gurobi/Python

APA Group; Sydney; Hybrid; AUD 140,000 - 190,000; Full time

Benefits offered by this job

Career development programs

Flexible working arrangements

Wellbeing initiatives

Parental leave (18 weeks)

Job summary

APA Group is seeking a Mathematical Optimisation Specialist to apply advanced modelling and optimisation to support operational and investment decisions across its Power business. The role focuses on turning complex constraints and commercial objectives into production‑ready optimisation solutions using Python and Gurobi, with a strong emphasis on cross‑functional collaboration.

The preferred location is Brisbane, with flexibility for Sydney or Melbourne.

Qualifications

• PhD in Mathematics or closely related quantitative discipline with strong mathematical modelling and optimisation foundation.
• Preference for an undergraduate electrical or mechanical engineering qualification.

Responsibilities

• Develop and own mathematical optimisation models to support operational and investment decision making, including dispatch optimisation, simulation and predictive modelling.
• Translate operational problems, constraints and commercial objectives into practical mathematical models using Gurobi and related optimisation techniques.
• Analyse asset performance, reliability trends and failure modes to identify opportunities to improve asset utilisation, efficiency and value.
• Develop, test, validate and deploy production ready optimisation solutions using Python, including scenario modelling and sensitivity analysis.
• Collaborate across engineering, operations and commercial teams to integrate optimisation models into operational decision making.

Skills

Python programming

Mathematical modelling

Stakeholder communication

Operations research

Problem solving

Education

PhD in Mathematics

Electrical/Mechanical engineering background (undergraduate)

Tools

Gurobi

Python

Job description

APA Group is seeking a Mathematical Optimisation Specialist to apply advanced modelling and optimisation to support operational and investment decisions across its Power business. The role focuses on turning complex constraints and commercial objectives into production‑ready optimisation solutions using Python and Gurobi, with a strong emphasis on cross‑functional collaboration.

The preferred location is Brisbane, with flexibility for Sydney or Melbourne.