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Hiring: Data Scientist – Mathematical Optimisation (Production-Grade OR)
United Kingdom (Hybrid – Heathrow Airport)
Full-Time
🌍 We welcome applications from all over The UK.
We are hiring a Data Scientist with deep expertise in Mathematical Optimisation / Operations Research to design and deploy large-scale decision systems within a complex, high-impact operational environment. This role is ideal for someone who enjoys translating real-world ambiguity into structured mathematical models and taking optimisation solutions from formulation through to production deployment.
🔎 What You’ll Be Working On
- Design and implement optimisation engines that directly power operational and commercial decision-making at scale across domains such as:
- Large-scale scheduling and resource allocation
- Network and fleet optimisation
- Disruption management
- Cost minimisation and efficiency modelling
- Multi-constraint planning systems
- Your work will move beyond academic modelling — these systems will be deployed into live production environments and embedded into critical workflows.
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🧠 Core Responsibilities
- Formulate and solve complex optimisation problems (LP, MILP, network flow, scheduling, heuristics)
- Build solver-based models using tools such as Gurobi, CPLEX, OR-Tools, Pyomo
- Translate business problems into structured mathematical formulations
- Develop scalable, production-ready optimisation systems in Python
- Collaborate with Data Engineers to productionise solutions via CI/CD and cloud pipelines
- Ensure models are robust, explainable, and operationally reliable
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✅ What We’re Looking For
- Strong background in Operations Research / Mathematical Optimisation
- Hands-on experience with LP/MILP modelling in production environments
- Experience with commercial or open-source solvers (Gurobi, CPLEX, OR-Tools, etc.)
- Strong Python development skills
- Experience deploying optimisation systems into live operational environments
- Ability to communicate complex modelling concepts to non-technical stakeholders
Nice to Have:
- Experience in aviation, transportation, logistics, or large-scale operational systems
- Knowledge of decomposition techniques (Benders, Column Generation)
- Exposure to cloud platforms (Azure, AWS, GCP)
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