Airport Capacity Planning Data Scientist

Airport Capacity Planning Data Scientist

Reports to: Process Information Manager

Location: London - Heathrow (All Terminals)

Contract Type: Permanent

We are seeking an experienced Capacity Planning Data Scientist to join the Airport Capacity & Planning team at Vanderlande, embedded within Heathrow Airport's baggage handling operations. This is a technically demanding role at the intersection of data science, operations research, and airport systems engineering.

• Develop and maintain machine learning models, simulation tools, and analytical frameworks that directly inform capacity planning decisions across one of the world's busiest airport baggage systems-processing in excess of 80 million bags annually across four terminals.
• Design, build, and validate machine learning models (e.g. XGBoost, GBM, random forests) for forecasting baggage volumes, capacity utilisation, and recirculation rates across all terminals.
• Engineer temporal and lag based features from high volume trace datasets (180M+ historical rows, 80,000+ daily ingestions) to improve model accuracy.
• Conduct hyperparameter tuning, cross validation, and model selection using rigorous statistical methods; target production grade performance metrics (e.g. R > 0.95, low RMSE/MAE).
• Develop time series decomposition and anomaly detection pipelines to identify emerging operational bottlenecks.
• Build and calibrate discrete event simulation (DES) models of terminal baggage systems to stress test capacity under various demand scenarios.
• Produce peak flow analyses, what if modelling, and scenario planning outputs to support infrastructure investment decisions and airline schedule changes.
• Translate complex analytical outputs into clear, actionable capacity recommendations for operational stakeholders and airline partners.
• Develop interactive Shiny applications and dashboards for real time and historical performance monitoring.
• Create publication quality reports and presentations using LaTeX and PowerPoint for senior leadership, airline customers, and Heathrow Airport Ltd stakeholders.
• Present findings to non technical audiences, distilling complex statistical concepts into clear operational insights.
• Stay current with advances in applied machine learning, operations research, and airport technology.
• Identify opportunities to apply AI/ML techniques (e.g. GPU accelerated training, LLM assisted analysis) to improve operational decision making.
• Contribute to the team's code standards, documentation, and reproducible research practices.

• Master's degree (or equivalent) in Data Science, Statistics, Operations Research, Computer Science, Mathematics, or a closely related quantitative discipline.
• Demonstrable portfolio of applied machine learning projects with real world datasets.
• Advanced proficiency in R programming, including tidyverse, data.table, caret/tidymodels, xgboost, and Shiny.
• Strong SQL skills with experience querying large scale relational databases (Azure SQL, PostgreSQL, or equivalent).
• Hands on experience with DuckDB or similar columnar/analytical databases for high performance local analytics.
• Solid understanding of supervised learning algorithms (gradient boosting, ensemble methods, regularised regression) with practical deployment experience.
• Experience with feature engineering for time series and operational data, including lag features, rolling aggregates, and temporal encoding.
• Proficiency in data pipeline development using Azure Data Factory, or similar orchestration tools.
• Proven ability to translate business problems into analytical frameworks and deliver actionable recommendations.
• Excellent written and verbal communication skills; comfortable presenting to senior leadership and external stakeholders.
• Strong problem solving mindset with attention to statistical rigour and reproducibility.
• Ability to work effectively within a team of 9 analysts while managing independent workstreams.
• Experience in aviation, airport operations, logistics, or baggage handling systems.
• Familiarity with discrete event simulation tools and methodologies.
• Knowledge of LaTeX for technical documentation and report generation.
• Experience with GPU accelerated machine learning (CUDA, cuML) or high performance computing environments.
• Exposure to version control (Git) and collaborative development workflows.
• Familiarity with Python as a secondary language for interoperability.

• 28 days annual leave (excluding public holidays)
• Bupa Medical Cover
• YuLife - Wellbeing membership with fast access to GP appointments, promotion of health and wellbeing along with daily quests to gain Yucoins that can be swapped for shopping vouchers
• A challenging work environment with lots of opportunities of career progression.
• Cycle to work scheme
• Yellow Nest is a salary exchange scheme that reduces childcare costs for parents and employers
• Pension with Aviva
• Access to Achievers an award winning recognition platform that inspires to recognise your coworkers where points are awarded that can be exchanged for a range of goods and discounts.

Vanderlande is an equal opportunity/affirmative action employer. Qualified applicants will be considered without regards to race, religion, color, national origin, gender, sexual orientation, age, marital status or disability status. If you feel there is a barrier that potentially prevents you from applying, we are always happy to discuss or explore, any reasonable adjustments can be made to support your application.