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