Principal Data Scientist - Optimisation Luton/Hybrid
When it comes to innovation and achievement there are few organisations with a better track record. With over 320 aircraft flying over 1000 routes to more than 30 countries, we’re the UK’s largest airline, the second largest in Europe and the eighth largest in the world. The Principal Data Scientist role is pivotal in transforming the company into a data-driven organization, responsible for supporting the implementation of the vision for the company's data science capabilities and ensuring the alignment of data-related projects with easyJet’s overall objectives.
This role is focused specifically on operational use cases – such as network planning, crew optimisation, maintenance, and disruption management – and the data science solutions delivered are expected to drive efficiency, resilience and cost-effectiveness in operational performance.
Responsibilities include managing and supporting data science resources, providing leadership employing Agile methodologies to deliver data science developments, and actively participating in hiring to build a robust data science team.
The role may involve expertise in either machine learning (e.g., The role demands leading the development and deployment of data science solutions, managing the entire project lifecycle, and collaborating with the Centre of Enablement (COE) to implement training and best practices.
Manage data science resource allocation within the team, ensuring optimal use of personnel and tools to meet project demands.
Provide technical support and guidance to data science team members, assisting in troubleshooting and resolving complex issues.
Apply Agile methodologies and a hypothesis-driven approach as required.
Take a lead role in hiring and building a high-performing team of Data Scientists.
Contribute to the recruitment and development of data talent across ITD&C and broader business functions.
Collaborate with the Data Management team to improve data quality and increase trust in analytical outputs.
Lead the development and deployment of data science solutions for a specific business area, ensuring alignment with strategic goals.
Lead the end-to-end delivery of data science projects, from gathering and shaping requirements to liaising with key stakeholders to identify and deliver appropriate solutions that meet project objectives.
Provide direction on tools and capabilities to optimise team performance and enhance overall efficiency, ensuring maximum productivity.
Own and define key performance indicators (KPIs) and diagnostics to measure performance against business goals, ensuring precise data-driven decision making.
Experience in coaching, training, or mentoring groups and individuals in both technical and developmental capacities.
Experience developing training materials in academic or business settings, particularly around data literacy (strongly preferred).
Commercial experience in Data and Analytics.
Proficiency in SQL (any variation).
Experience using Python to extract, manipulate, and summarize data from large databases.
time series analysis, multivariate analysis, forecasting) and/or mathematical optimisation methods (e.g., linear programming, constraint programming, heuristic approaches).
Experience working in cross-functional teams and projects.
Experienced in using a wide range of coaching and mentoring skills to support peers and individuals across the broader business.
Competitive base salary
~ Up to 30% bonus
~25 days holiday
~ BAYE, SAYE & Performance share schemes
~7% pension
~ Life Insurance
~ Work Away Scheme
~ Flexible benefits package
~ Excellent staff travel benefits
At easyJet our aim is to make low-cost travel easy – connecting people to what they value using Europe’s best airline network, great value fares, and friendly service.
It takes a real team effort to carry over 90 million passengers a year across 35 countries. We see people first and foremost for their performance and potential and we are committed to building a diverse and inclusive organisation that supports the needs of all.