Lead Data Scientist - Optimisation Engineering

easyJet Airline Company PLC; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

easyJet Airline Company PLC is seeking a Principal Data Scientist to lead an optimisation engineering team that builds decision-support products for disruption management and crew rostering.

You will translate operational problems into scalable software and optimisation solutions, partnering with product, OR, and stakeholders, while shaping architecture, delivery, quality and reliability.

Qualifications

• Led a software engineering team delivering production-grade systems with solver tech.
• Strong fundamentals in system design, distributed systems, APIs, data modeling and ops.
• Experience in optimization, scheduling or decision-support with constraint-based reasoning.
• Knowledge of MILP, constraint programming or heuristics and their product impact.
• Hands-on programming in Python, Java, C#, or C++, with code-review guidance.

Responsibilities

• Lead a cross-functional team of software engineers and OR/data science specialists.
• Own technical direction for models that optimise disruption and crewing problems.
• Drive architecture for services, data pipelines, and user workflows at scale.
• Collaborate with product management to shape roadmap and measurable outcomes.
• Integrate solvers (Gurobi/CPLEX) and ensure model performance and explainability.
• Promote engineering excellence: tests, CI/CD, releases, incidents, learning.

Skills

Leadership

Software engineering

Optimization software

Python

Java

C++

C#

Tools

Gurobi

CPLEX

Job description

Job Description - Principal Data Scientist - Optimisation Engineering (17233)

Job Description

Principal Data Scientist - Optimisation Engineering ( 17233 )

Description

Principal Data Scientist - Optimization Engineering

We are easyJet – a FTSE-250 listed, £multi-billion low-cost airline that serves tens of millions of customers every single year. If you’re reading this, you have probably already been an easyJet customer, and you’ll know that there is no more iconic (or Orange!) travel brand in Europe. We fly more than 1,207 routes, connecting 38 countries across Europe, and employ more than 18,000 colleagues. We’re on a mission to make low-cost travel easy – and whatever your role here, you’ll connect millions of people to what they love using Europe’s best airline network, great value fares, and friendly service. What makes us easyJet? Our Promise Behaviours – we are Safe, Bold, Welcoming and Challenging. Four Behaviours. One Spirit. One easyJet.

Role summary Lead an optimisation engineering team building decision-support products that solve complex disruption-management and crew/roster optimisation challenges. You’ll translate operational problems into scalable software and optimisation solutions, partnering closely with product, data/operations research (OR), and customer stakeholders. The role blends people leadership with hands-on technical direction across architecture, delivery, quality, and reliability.

Requirements of the Role

Key responsibilities

• Lead, coach, and grow a cross-functional team of software engineers (and closely partnered OR/data science specialists)
• Own technical direction and delivery for products that model, optimise, and operationalise solutions to disruption and crewing problems (e.g., recovery planning, re-optimisation, what-if analysis).
• Drive architecture and design decisions for services, APIs, data pipelines, and user-facing workflows that support optimisation at scale.
• Partner with product management to shape roadmap, break down ambiguous problem statements, and define measurable outcomes and acceptance criteria.
• Collaborate with OR/optimisation experts to integrate solvers (e.g., Gurobi) and ensure model performance, correctness, explainability, and maintainability.
• Establish strong engineering practices: code review, automated testing, CI/CD, release management, incident response, and post-incident learning.
• Build observability into optimisation services (KPIs, logs, traces) and manage performance tuning (latency, throughput, cost) across environments.
• Contribute hands-on when needed (prototyping, critical-path coding, reviews), while primarily enabling the team to deliver consistently.

Required qualifications

• Proven experience leading a software engineering team delivering production-grade systems (people leadership and/or strong technical leadership), that encompass solver technology (like CPLEX or Gurobi).
• Strong software engineering fundamentals: system design, distributed systems concepts, APIs, data modelling, testing, and operational excellence.
• Experience building optimisation, scheduling, or decision-support applications, or closely related domains requiring complex constraint-based reasoning.
• Working knowledge of mathematical optimisation concepts (e.g., MILP, constraint programming, heuristics/metaheuristics) and how they impact product design.
• Hands-on programming experience in one or more mainstream languages (e.g., Python, Java, C#, C++), with the ability to review and guide code quality.