Lead Data Scientist - Optimisation (Contract | Inside IR35) Location: London / Midlands (Hybrid occasional European travel) Rate: £500 per day (Inside IR35) A leading consultancy is delivering a major analytics transformation programme for a global transportation organisation. They are looking for a Lead Data Scientist with deep optimisation expertise to drive high-impact decisioning solutions. This is not a generic ML role. The focus is on advanced optimisation modelling applied to real-world operational problems at scale. The Role You will take ownership of complex optimisation initiatives, working closely with business, product, and engineering teams to design and deploy production-grade models. Key responsibilities: Lead the design and implementation of optimisation models across multiple business domains Translate complex operational challenges into mathematical frameworks Build scalable, production-ready solutions end-to-end Collaborate with cross-functional teams to influence decision-making Communicate trade-offs and model outputs clearly to senior stakeholders Provide technical leadership and mentor other data scientists Ensure robustness, scalability, and performance of deployed models What You'll Bring (Essential) Strong, hands-on experience building and deploying optimisation models in industry: Linear Programming (LP) Mixed Integer Programming (MIP) Constraint optimisation Network, scheduling, or resource optimisation Proven track record applying optimisation to real business problems Advanced Python skills with tools such as Pyomo, PuLP, OR-Tools, Gurobi, or CPLEX Strong grounding in mathematics, statistics, and algorithms Experience working with large, complex datasets and constraints Ability to lead solution design and drive delivery Important: This role requires deep optimisation expertise. It is not suited to candidates focused primarily on machine learning models or dashboards. Nice to Have Experience with simulation or scenario modelling Ideally experience within aviation, airline, or closely related industries Background in logistics, supply chain, pricing, or large-scale operations Cloud deployment experience (AWS, Azure, or GCP) Experience mentoring or leading teams Education Master's degree or PhD in a quantitative field such as Operations Research, Data Science, Mathematics, Statistics, or Engineering Why Apply High-impact work on large-scale, real-world optimisation problems Opportunity to shape decision-making in a complex operational environment Long-term programme with strong extension potential