Data Scientist - Applied Optimisation

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The opportunity

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

In line with client requirements this role is based in our Boorloo – Perth, Australia office.

Our roles can potentially be adjusted to work flexibly with reduced hours. Please speak with us about potential options.

Your Key Responsibilities

• Develop and maintain large‑scale LP / MIP optimisation models for mine planning and scheduling.
• Design and implement constraints
• 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 stakeholder.

Skills And Attributes For Success

Ideally, you’ll have the skills and attributes below, but don’t worry if you don’t tick all the boxes. We’re interested in your aptitude, attitude and willingness to learn.

• 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.
• Mine planning, supply chain, or heavy industry optimisation.
• Graph based or network flow optimisation.

Core tech stack:

• Optimisation methods (linear programming, mixed integer programming, Network / flow-based optimisation, Constraint based modelling)
• Programming and modelling (python, ampl modelling language), working knowledge of C# / .Net

What We Offer You

At EY, we’ll fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. We’re proud to be recognised as the #1 WORK180 Endorsed Employer in the Top 101 Employers for Women 2026. Learn more.

• Career development: At EY, your career is yours to shape! We’ll develop you with future-focused skills and equip you with world-class experiences ey.com/au/careerdevelopment
• Flexible work arrangements: Our flexible work policies empower you to balance your professional and personal life, fostering a culture of trust and autonomy.
• A comprehensive benefits package: From a yearly wellness incentive, to access to additional 8 weeks of flex leave per year, and family-friendly policies, including up to 26 weeks of gender-neutral paid parental leave, we cater to your diverse needs to help you thrive both personally and professionally www.ey.com/au/benefits    

Acknowledgement of Country

EY acknowledges the Traditional Owners and Custodians of the lands on which EY offices are located around Australia. We pay our respects to their cultures, and to their Elders — past, present, and emerging. Find out more about our vision for reconciliation at ey.com/en_au/careers/indigenous

Inclusiveness is core to who we are and how we work together, driving value for our people and for our business. We encourage applications from people of all ages, nationalities, abilities, cultures, sexual orientations, and gender identities and are committed to providing an equitable and barrier free recruitment experience for all. We encourage you to share any support and adjustments you need to be your best and participate equitably in our recruitment process. We understand sharing your needs with us can be daunting, so if you have questions before or during your application, we welcome you to get in touch at [email protected] or +61 3 8650 7788 (option 2). Anything you tell us will be kept completely confidential.

Are you ready to shape your future with confidence? Apply today.

EY | Building a better working world

Our preferred applicant will be required to undertake employment screening by EY or our external third-party provider.

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