Data Scientist (Operational Research)

TL;DR

Data Scientist (Operational Research): Developing data pipelines, machine learning models, and complex optimization models for an aviation decision-support product suite with an accent on operational research and mathematical programming. Focus on industrializing models in Python, optimizing resource use for airlines, and translating operational challenges into analytical solutions.

Location: Must be based in the UK or Europe

Company

A fast-growing travel technology company helping airlines modernize their operating models using cloud, data, and AI to maximize operational efficiency.

What you will do

• Design, build, and deploy data science and optimization models for operational domains like workforce planning and supply chain.
• Own use cases end-to-end, from problem definition and modeling to experimentation and production delivery.
• Prototype and industrialize machine learning and optimization models in Python, following software engineering best practices.
• Build and maintain robust data pipelines, including testing, logging, and CI/CD for production-grade solutions.
• Engage directly with business stakeholders to translate operational challenges into analytical solutions.
• Contribute to feature prioritization and roadmap discussions to balance speed and long-term value.

Requirements

• Recent commercial experience with Operational Research and optimization techniques (linear, non-linear, mixed-integer programming, constraint satisfaction).
• Proficiency in Python and optimization/data libraries such as SciPy, OR-Tools, Gurobi, CPLEX, Pandas, and NumPy.
• Solid data engineering skills, including SQL and the ability to build data pipelines.
• Experience productionizing models using cloud platforms (AWS preferred), experiment tracking, and workflow orchestration.
• Must be based in the UK or Europe.
• Excellent communication skills to engage confidently with non-technical stakeholders.

Nice to have

• Background in operations-heavy industries such as aviation, logistics, supply chain, or retail.
• Systems thinking and a pragmatic, data-driven approach to problem-solving.

Culture & Benefits

• Flexible working environment with remote team options.
• Opportunities for career advancement and professional learning and development.
• Inclusive community committed to diversity, equity, and inclusion.
• Competitive salary based on experience.