Data Scientist - Applied Optimisation

4w1 month ago

Perth, AU · Full-time · A$140,000 – A$180,000

About this role

As a manager-ranked Data Scientist within EY's AI & Data service line, you will design, extend, and validate large-scale mathematical optimisation models supporting strategic mine planning and optimisation platforms. This role focuses on solving complex, high-impact planning problems using advanced optimisation techniques to support long-term operational and investment decisions.

Day-to-day, you will develop and maintain large-scale LP/MIP optimisation models for mine planning and scheduling, design and implement constraints, and integrate and tune commercial solvers to ensure performance, stability, and correctness. You will also validate optimisation results through testing, cross-checks, and alternative formulations, and diagnose and resolve infeasible, unstable, or slow-running models.

You will collaborate closely with product, engineering, and domain experts to translate business requirements into robust mathematical models. You will also clearly communicate optimisation outcomes, assumptions, and trade-offs to both technical and non-technical stakeholders, working within a globally connected team of diverse experts.

This role offers the opportunity to shape your future with confidence in a globally connected powerhouse of diverse teams. EY is committed to helping you succeed and take your career wherever you want it to go, while contributing to building a better working world.

Requirements

Strong background in Operations Research, Applied Mathematics, and Optimisation
Hands-on experience with mixed-integer and linear programming in production settings
Proven use of commercial optimisation solvers
Strong Python skills for model development, solver integration, and testing
Experience working with large, complex datasets and performance-critical optimisation problems
Ability to own solution correctness and defend optimisation outputs
Experience in mine planning, supply chain, or heavy industry optimisation
Experience with graph-based or network flow optimisation

Responsibilities

Develop and maintain large-scale LP/MIP optimisation models for mine planning and scheduling
Design and implement constraints for complex optimisation problems
Integrate and tune commercial solvers to ensure performance, stability, and correctness
Support advanced optimisation workflows
Validate optimisation results through testing, cross-checks, and alternative formulations
Diagnose and resolve infeasible, unstable, or slow-running optimisation models
Collaborate with product, engineering, and domain experts to translate business requirements into robust mathematical models
Clearly communicate optimisation outcomes, assumptions, and trade-offs to technical and non-technical stakeholders