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