Data Scientist Manager

Data Scientist Manager at Changi Airport Group

This role primarily focuses on data science development and delivery, while also supporting AI enablement and training initiatives to build organization-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.

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.

Key skills/competency

• Data Science
• Machine Learning
• Python
• SQL
• TensorFlow
• PyTorch
• Scikit-learn
• Data Visualization
• Stakeholder Engagement
• AI Governance