Junior Optimisation Analyst

About the role

The Junior Optimisation Analyst, Business Analytics will turn data into business insights. Using data and advanced operational research techniques – including optimisation, simulation, and predictive modelling – you’ll apply mathematical thinking to solve real-world problems across the airport.

You’ll work closely with a team of analysts and operational performance leads to understand business needs and build robust solutions. Your aim is to equip decision makers with the most confident information as effectively and efficiently as possible, positioning the business for excellent customer service. Your work will directly influence airport operations, capacity planning, and customer experience; making a measurable difference in how the airport runs.

You can find out more about the team here

About the Recruitment Process

The recruitment process for this role will be comprised of 3 stages.

• Online assessment to test key competencies and skills required for the role
• An analysis task, and Teams interview to discuss your findings, experience and interest in the role
• An in person interview, where we will ask competency, values and technical questions

You can find out more about our interview process, and the type of questions we may ask here.

What you’ll be doing

• Collaborate with analysts and cross functional business stakeholders to study operational processes and identify opportunities for efficiency and optimisation.
• Build and maintain models that realistically reflect operational constraints and demand to inform future build requirements, staffing structure, and operating processes.
• Derive long and short-term demand forecasts and predictive analytics across operational areas of the airport
• Translate business problems into mathematical formulations and develop optimisation based decision-support tools that balance efficiency, cost, and customer experience.
• Source, identify, test, tidy, and optimise datasets for straightforward use across platforms. Investigate data discrepancies to improve data quality. Transform large datasets into accessible insights that simplify business decision making.
• Develop data visualizations, dashboards, and reporting in Tableau (or a similar tool). Troubleshoot and resolve any reporting and dashboarding issues.
• Ensure performance leads and business owners have access to the most accurate information.
• Conduct exploratory data analysis, establish KPIs, and provide descriptive analytics of past trends.
• Simply and concisely present results and recommendations to business stakeholders (both written and verbal).
• Support the Business Analytics team with ad-hoc and bespoke analysis.
• Support the analytical requirements of capital projects across the operation.

What we’re looking for

We are looking someone passionate about data analytics, optimisation, and supporting the continuous improvement of business operations in a fast-paced organisation.

Key skills:

• Problem solving: you enjoy the challenge of solving complex problems and deploying practical solutions.
• Curiosity: you have a desire to understand how things work and how we can make them better.
• Precise: you enjoy manipulating large and numerous datasets and have excellent attention to detail.
• Team player: you have strong interpersonal skills and ability to communicate effectively.
• Savvy: Ability to learn quickly, use and/or develop the latest capacity modelling software, reporting tools, and statistical techniques.
• Self-starter: Able to work independently, run with tasks on your own, and confident to make decisions

Credentials and Experience

• Essential: Recently completed a degree with a strong STEM focus such as Engineering, Mathematics, or Data Science with a specific specialisation in Operational Research or Optimisation.
• Essential: Proficient in Microsoft Office, especially Excel and PowerPoint.
• Essential: Experience in data science programming languages such as R, Python, SQL.
• Essential: Highly numeric with proven analytical and problem-solving skills. Understanding and experience with optimisation techniques (e.g. linear programming, integer programming, network optimisation) and relevant software or libraries (such as Pyomo, PuLP, or commercial solvers like Gurobi, CPLEX, or FICO Xpress).
• Desirable: experience with dashboarding software such as Tableau.

If your experience looks slightly different to what we’ve listed here, we encourage you to still apply. You could add something we didn’t know we needed.