Senior Data Scientist - Optimisation

The Senior Data Scientist (Optimisation)

Will lead the design, development and deployment of mission-critical optimisation solutions that drive operational excellence across the airline. This role demands deep expertise in mathematical programming, advanced optimisation techniques, and production-grade implementation using solvers such as Gurobi or IBM CPLEX. You will architect solutions for complex routing, scheduling, and resource allocation problems while mentoring team members and establishing optimisation best practices.

This role requires proven experience delivering optimisation solutions in operational environments. Candidates with airline industry experience or comparable domains (transport operations, logistics networks, crew/aircraft scheduling) will be particularly valued.

• Lead the architecture and delivery of optimisation solutions (linear programming, mixed-integer programming, graph algorithms, constraint programming) for crew planning, aircraft scheduling, routing, and operational decision-making.
• Design and implement high-performance algorithms in C++ and Python, optimising for both solution quality and computational efficiency with industry-standard solvers (Gurobi/CPLEX).
• Define technical strategy for optimisation capability, evaluating emerging techniques (column generation, decomposition methods, hybrid approaches) and tooling.
• Lead integration of optimisation with simulation and reinforcement learning to solve multi-stage decision problems.
• Partner with senior stakeholders across Operations, Planning, Crew, and Engineering to translate business challenges into tractable mathematical models with quantifiable ROI.
• Present complex technical solutions and trade-offs to leadership, translating optimisation concepts into business impact.
• Lead Agile delivery across the full Data Science lifecycle, from opportunity identification through production deployment and continuous improvement.
• Drive collaboration with Data Management to ensure data quality and availability for optimisation pipelines.
• Mentor data scientists in operations research techniques, conduct technical reviews, and build optimisation capability across the team.
• Represent the organisation at industry conferences and academic partnerships, staying at the forefront of optimisation research and practice.

• Expert knowledge of operations research, mathematical programming, and optimisation theory.
• Advanced proficiency in Python and C++ (or similar high-performance languages) for production-grade model development.
• Deep hands‑on experience with Gurobi and/or IBM CPLEX, including advanced features (callbacks, tuning, decomposition).
• Proven track record delivering optimisation solutions for routing, scheduling, or resource allocation in operational environments. Airline or transportation/logistics experience highly valued.
• Experience with large-scale optimisation and techniques for managing computational complexity.
• Strong understanding of algorithm design, computational complexity, and performance optimisation.
• Excellent communication and influencing skills, with ability to explain sophisticated mathematical concepts to diverse audiences.
• A degree in Operations Research, Mathematics, Computer Science, Engineering or related quantitative discipline.
• Demonstrated leadership in cross‑functional teams and ability to drive consensus on technical decisions.
• Relevant experience with operations research and optimisation in industry settings, with demonstrable progression in technical leadership.

• Experience with cloud-based optimisation platforms and distributed computing.
• Knowledge of machine learning and hybrid optimisation/AI approaches.
• Familiarity with simulation, reinforcement learning, heuristic and metaheuristic methods.
• Experience with commercial airline operations, crew planning systems, or aircraft scheduling.

If you are a self-starter who can identify opportunities to drive greater success for the team and have a track record of building strong relationships with internal stakeholders, we would love to hear from you. Apply now to join our dynamic team!