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Data Scientist – Optimisation
Role Overview
Design and scale large optimisation models for strategic mine planning, solving complex scheduling, blending, and capacity problems to support long-term operational decisions
Key Responsibilities
- Develop and maintain with linear programming/ mixed integer programming/ network/flow-based optimisation models
- Model constraints (capacity, sequencing, blending, costs, boundaries, etc.)
- Integrate and tune optimisation solvers
- Diagnose infeasibility, performance, and stability issues
- Validate outputs via testing, cross-checks, and alternative formulations
- Collaborate with product and domain teams to translate requirements into models
- Own solution correctness and justify optimisation outputs.
Required Skills
- Strong background in Operations Research / Optimisation and mining
- Experience with linear programming and mixed integer programming in production environments
- Proven record of hands-on experience with commercial solvers (Gurobi, AMPL, Maroma)
- Experience working with large, complex datasets and performance‑critical optimisation problems
- Robust Python for model development and integration
- Experience with large-scale optimisation problems
Core Tech Stack
- Solvers: Gurobi, AMPL, Maroma
- Techniques: LP, MIP, Network/Flow optimisation, Constraint modelling
- Languages: Python, AMPL
Nice to Have
- Familiarity with Mine planning or heavy industry optimisation
- Exposure to Large scheduling problems
- API / platform integration experience
- Exposure to stochastic optimisation
- Exposure to C#/.NET
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