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

- Solid 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 performancecritical optimisation problems
- Strong 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

📌 EY - GDS Consulting - AI And DATA - Data Scientist - Opt - Manager (Bengaluru)
🏢 EY
📍 Bengaluru