Data Scientist

Role: Data Scientist Location: Waterside, Heathrow (Hybrid work and Travel to Europe occasionally) Contract We are looking for a true Data Scientist with strong optimization expertise to lead advanced analytical and optimization initiatives. The role will focus heavily on building, deploying, and scaling optimization models, which is a hard requirement from the Business Analytics (BA) team, given the nature of work planned for London. Experience Expectations • 10–12+ years in advanced analytics / data science roles. • At least 4–6 years of hands-on optimization modeling experience. • Demonstrated ability to lead solution design, not just execute tasks. Key Responsibilities • Lead the design and development of optimization models (linear, non-linear, mixed-integer, stochastic, heuristic-based). • Translate complex business problems into mathematical and optimization frameworks. • Work closely with Business Analytics, Product, and Engineering teams to drive decision-making. • Develop end-to-end data science solutions: data exploration, feature engineering, modeling, validation, and deployment. • Guide and review work of junior data scientists and analysts. • Communicate model outcomes and trade-offs clearly to senior stakeholders. • Ensure scalability, performance, and robustness of models in production. Mandatory Skills (Hard Requirements) • Strong hands-on experience in Optimization models (must-have): • Linear Programming (LP) • Mixed Integer Programming (MIP) • Constraint Optimization • Network / Scheduling / Resource Optimization • Proven experience applying optimization in real business scenarios, not just academic projects. • Advanced proficiency in Python (Pyomo, PuLP, OR-Tools, Gurobi, CPLEX, or similar). • Strong foundations in statistics, mathematics, and algorithms. • Experience working with large datasets and complex problem constraints. • Note: This role is not suitable for profile-heavy ML / dashboard-focused candidates without real optimization experience. Good-to-Have Skills • Exposure to simulation techniques and scenario modeling. • Experience in industries like aviation, logistics, supply chain, pricing, operations research, or large-scale planning. • Cloud experience (AWS / Azure / GCP) for model deployment. • Experience leading teams or acting as a technical mentor.