Title: Data Scientist (Manager), Airport Operations Technology & Corporate IT
This role focuses primarily on data science development and delivery, while also supports AI enablement and training initiatives to build organisation-wide AI awareness and adoption. The ideal candidate is hands-on with data science projects, yet comfortable engaging stakeholders and helping to upskill colleagues in responsible and effective AI use.
Key Responsibilities
Data Science
· Deliver end-to-end data science projects, including data collection, processing, feature engineering, model building, testing, deployment, and monitoring.
· Collaborate with product owners, engineers, and business stakeholders to define requirements, translate needs into solutions, and ensure measurable impact.
· Perform exploratory data analysis and communicate findings to both technical and non-technical audiences.
· Design, build, and validate machine learning models and algorithms to support airport operations and business functions.
· Ensure quality, scalability, and responsible use of data science solutions.
· Provide technical guidance to one junior data scientist in the team.
AI Education & Training
· Support the design and delivery of AI awareness and training programmes to upskill staff across the organisation.
· Contribute to the development of best practices, guidelines, and governance for safe and responsible adoption of AI solutions.
· Keep abreast of emerging AI technologies, tools, and industry trends to share knowledge and inspire adoption.
· Work with business units to promote AI “smart adoption” and help staff better leverage AI-driven tools in their work.
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Requirements
· Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field. Master’s degree preferred.
· At least 5 years of experience in data science, with proven track record in delivering end-to-end projects.
· Strong proficiency in Python, SQL, and machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
· Experience with data visualisation and communicating insights to non-technical stakeholders.
· Knowledge of AI governance, ethics, or training design is a plus.
· Strong interpersonal and communication skills; able to collaborate across functions and engage diverse stakeholders.