Data Scientist

Senior Data Scientist (Optimisation & Operations Research) Role Title: Senior Data Scientist – Optimisation Location: Waterside, UK (hybrid) Contract Type: Contract (Inside IR35) Travel: Occasional travel to Europe required Eligibility: UK or EU Citizens only (mandatory) Role Overview We are seeking a senior-level Data Scientist with deep optimisation and operations research experience, ideally within airline, aviation, or complex logistics environments. This role sits within a product-led, cross-functional squad responsible for building industrialised decision-support software used in operationally critical environments. The successful candidate will design, develop, and productionise optimisation and machine learning models that directly influence real-world operational decisions. This is not a generic ML role — strong mathematical optimisation, structured problem-solving, and stakeholder engagement are core to success. Key Responsibilities Optimisation & Modelling • Design and implement advanced optimisation and decision-support models (e.g. LP, MIP, heuristics, metaheuristics). • Translate complex operational problems into mathematical formulations with clear objectives and constraints. • Prototype, test, and refine optimisation and ML models in Python. • Harden models for operational use, including edge cases and data anomalies. Full-Stack Data Science Delivery • Build and maintain robust data pipelines using Python and SQL. • Industrialise models following software engineering best practices: • modular design • strict typing • unit and regression testing • Integrate algorithms into workflow orchestration frameworks (e.g. Dagster or Airflow). • Collaborate with engineers to ensure models integrate seamlessly into the wider product stack (data ingestion, UI, orchestration). Product & Business Engagement • Work closely with business stakeholders to understand decision-making processes, constraints, and trade-offs. • Clearly explain optimisation approaches, assumptions, and results to non-technical audiences. • Quantify and communicate business value and impact (e.g. cost savings, efficiency gains). • Contribute to feature prioritisation, balancing speed of delivery vs long-term value. Ways of Working • Operate effectively within an Agile product squad. • Use Git best practices for version control, peer reviews, and documentation. • Take ownership of delivery with minimal supervision. • Mentor junior data scientists where required. Required Skills & Experience (Must-Have) • Proven experience in optimisation / operations research (not just predictive ML). • Strong Python skills with OR and DS libraries (e.g. pandas, numpy, scikit-learn, gurobi, ortools). • Ability to structure ambiguous operational problems and reason through trade-offs. • Experience delivering production-grade data science software. • Strong communication skills with both technical and non-technical stakeholders. • Experience working in large-scale, complex, data-intensive environments. • Eligible for travel within Europe (citizenship required). Desirable Experience (Nice-to-Have) • Airline, aviation, transportation, or logistics domain experience. • Exposure to safety-critical or regulated operational environments. • Cloud experience (AWS preferred), CI/CD pipelines, Docker, workflow orchestration. • Consulting or advisory background. • Experience mentoring or leading other data scientists. Qualifications • Master’s degree (or higher) in Data Science, Operations Research, Applied Mathematics, or related field • OR • Equivalent relevant industry experience with a strong optimisation focus What Success Looks Like • Optimisation models are robust, explainable, and operationally trusted. • Clear linkage between technical solutions and business outcomes. • High-quality, maintainable code deployed through standard engineering pipelines. • Strong collaboration across product, engineering, and business teams.