Mathematical Optimization Data Scientist

Hiring: Data Scientist – Mathematical Optimisation (Production-Grade OR)

United Kingdom (Hybrid – Heathrow Airport, 1x per month onsite)

Full-Time

🌍 We welcome applications from candidates worldwide. Full visa sponsorship and relocation support will be provided for the successful candidate.

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

You will 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

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• 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.

🧠 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

✅ 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)