Python Job: Data Scientist

As Data Scientist, you’ll be the technical expert for demand forecasting and airport capacity at Heathrow. Providing data analytics and advanced modelling, you’ll support operational planning and help inform strategic problem solving. You’ll develop complex models and methodologies, ensuring Heathrow’s forecasting capability is world class, using cutting edge tools and techniques such as machine learning, and drive efficiency through automation.

Your role will involve:

• Delivering accurate forecasting and capacity analysis to enable the efficient planning and operation of the airport.
• Turning data analysis output into informed insight and implication for the airport, making reasoned judgements and recommendations based on uncertain information in a commercially and operationally intelligent way.
• Presenting complex ideas, evidence and technical outputs concisely, accurately and clearly, to stakeholders - often a non-technical audience.
• Introducing processes to maximise quality and efficiency, making use of automation tools to promote a self-service approach to analytics adoption.
• Working with the airport community to ensure access to data sources and tools that enable development and improvement to models and methodologies.
• Develop, maintain and monitor complex forecasting models and dashboards.

These skills are essential:

• Previous experience in Data Science is essential – ideally previous experience working as a Data Scientist, but we would also consider someone with a degree in Data Science.
• Advanced technical and analytical competence.
• Object oriented programming experience is crucial, particularly in R, Python, SQL,
• Able to quickly learn new analytical tools such as PowerBi
• A good understanding of Spark & Hadoop
• A good knowledge of forecasting, machine learning and data modelling approaches.

Ideally, you'll also have:

• Broad knowledge of Databricks
• Knowledge of Heathrow, or at least a broad interest in aviation.
• Good team working skills, able to manage and plan own work and to work under tight time deadlines