Data Scientist - Applied Optimisation

About EY and the Role

EY is seeking a manager-level Data Scientist to join its AI & Data practice in Perth, where the focus is on building confidence in future careers while contributing to work that helps shape a better world. In this position, you will create, expand, and verify large-scale mathematical optimisation models that support strategic mine planning and optimisation platforms. The work centres on solving complex, high-impact planning challenges through advanced optimisation methods that inform long-term operating and investment decisions. This position is based at EY’s Boorloo (Perth, Australia) office, in line with client needs.

There is also an option for flexible arrangements, including reduced hours, subject to discussion with the team.

Key Responsibilities

• Build and support large-scale linear programming and mixed-integer programming models for mine planning and scheduling.
• Create and apply model constraints.
• Connect commercial solvers into the workflow and refine them for speed, reliability, and accuracy.
• Support advanced optimisation processes and tooling.
• Check outputs through testing, cross-verification, and comparison with alternate model designs.
• Investigate and fix models that are infeasible, unstable, or too slow to run effectively.
• Work closely with product, engineering, and subject-matter specialists to convert business needs into mathematically sound models.
• Explain optimisation results, assumptions, and trade-offs clearly to both technical and non-technical stakeholders.

Skills and Attributes

• Strong grounding in operations research, applied mathematics, and optimisation.
• Practical experience using linear and mixed-integer programming in production environments.
• Experience with commercial optimisation solvers.
• Solid Python skills for model building, solver integration, and testing.
• Comfort working with large, complex data sets and performance-sensitive optimisation problems.
• Ability to take ownership of solution correctness and justify model outputs.
• Exposure to mine planning, supply chain, or heavy-industry optimisation.
• Familiarity with graph-based or network-flow optimisation.
• Working knowledge of optimisation methods such as linear programming, mixed-integer programming, network/flow-based optimisation, and constraint-based modelling.
• Programming and modelling experience with Python and AMPL, plus working knowledge of C#/.NET.

What EY Offers

• Career development opportunities with future-focused learning and broad, world-class experiences.
• Flexible working arrangements that support balance and autonomy.
• A comprehensive benefits package that includes a yearly wellness incentive, up to 8 additional weeks of flex leave per year, and family-friendly policies with up to 26 weeks of gender-neutral paid parental leave.

Equal Opportunity and Additional Information

EY values inclusion and welcomes applications from people of all ages, nationalities, abilities, cultures, sexual orientations, and gender identities. The company is committed to providing a fair and accessible recruitment process and encourages candidates to request any adjustments they may need. Any support needs shared during the process will be kept confidential.

The preferred candidate will need to complete employment screening conducted by EY or an external third-party provider. EY also acknowledges the Traditional Owners and Custodians of the lands on which its offices are located across Australia and recognises their cultures and Elders past, present, and emerging.

Applicants should be prepared to undertake the required screening as part of the hiring process.