Senior Data Scientist

Job description: Senior Data Scientist

Client Airport’s Advanced Analytics & AI function turns operational and commercial data into decisions across parking, aeronautical, retail and airport operations. As a Senior Data Scientist you own our highest value data science use cases end-to-end — from framing the problem with business owners through to deploying and monitoring production models — and act as the trusted technical advisor bridging the business and our onshore/offshore delivery team.
KEY RESPONSIBILITIES
Lead delivery of forecasting and optimisation use cases such as car-park occupancy and price-elasticity modelling, valet resource optimisation, 18-month and 5-year passenger (PAX) forecasts, ML security-screening forecasts, and retail PSR and cross-sell models. Partner directly with business owners across Parking, Commercial/Aero, Retail and Operations to frame problems, define success measures, and translate model outputs into pricing, capacity, staffing and revenue decisions. Design, build, validate and productionise models in Python on our data science platform (Azure Machine Learning), integrated with Snowflake. Own model quality and the full lifecycle — feature engineering, explainability and what-if analysis, batch prediction, and production monitoring for data drift and model health. Present forecasts, insights and recommendations to senior stakeholders and executives, and run scenario analysis to support high-stakes decisions (e.g. capacity build vs no-build, pricing strategy). Set technical direction and mentor onshore and offshore data scientists; review work and lift delivery standards.
SKILLS & EXPERIENCE — ESSENTIAL
7+ years’ applied data science, with a track record of models deployed to production and adopted by the business. Expert in Python (pandas, scikit-learn and related ML/stats libraries) and SQL, with a strong foundation in timeseries forecasting, regression, classification and clustering. Hands-on experience with an enterprise ML platform (Azure ML or equivalent AutoML) and a cloud data warehouse (Snowflake or equivalent). Proven MLOps discipline — model deployment, batch-prediction pipelines, monitoring, drift detection and retraining. Working experience on Microsoft Azure (e.g. Azure ML, Azure DevOps, storage and compute services). Excellent stakeholder engagement and data storytelling — able to turn technical results into commercial decisions and present with confidence to executives. Degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Engineering or Data Science) or equivalent experience.
DESIRABLE
Aviation, transport, or pricing / revenue-management and forecasting-heavy operational domains. Power BI, explainable AI, optimisation, and A/B testing frameworks. Familiarity with Responsible AI governance and privacy-aware analytics. Experience leading or mentoring distributed onshore/offshore teams.
OUR TOOLS & ENVIRONMENT
Python · SQL · Microsoft Azure Machine Learning · Snowflake · Power BI · Azure Cloud