[What the role is]
You will be part of CAAS’s data team, which drives data management, engineering, science and Artificial Intelligence (AI) use cases across the organisation. The data science team focuses on complex problems requiring strong technical, data science expertise, including predictive and prescriptive modelling, optimisation, and AI-enabled decision systems at enterprise (CAAS) and ecosystem (Air Hub) scale.
You will collaborate with other divisions to apply advanced data science techniques to solve business problems, and design, build and operationalise Machine Learning (ML) and AI solutions across the full lifecycle — from problem framing and experimentation to deployment and monitoring. The scope includes machine learning, multimodal AI, generative AI, and agentic workflows.
[What you will be working on]
- Partner divisions to identify, translate, and deliver high-value business problems into clear data science problem statements and evaluation metrics.
- Design and develop ML and AI solutions for complex operational, regulatory and planning problems.
- Apply techniques such as predictive modelling, optimisation, simulation, and agentic workflows where appropriate.
- Experiment and build prototypes to assess feasibility, performance and deployment readiness.
- Evaluate models and solutions for performance, robustness, and drift, ensuring they are reliable and ready for operational use.
- Work with engineering teams and vendors to productionise and refine solutions.
- Perform advanced analytics, including techniques such as clustering, segmentation, anomaly detection and other exploratory methods, for complex problems that divisions are unable to address themselves.
- Build data pipelines, feature engineering workflows, and model training and inference processes with data engineers.
- Collaborate with research institutes and external vendors in the design and delivery of AI and data science solutions.
[What we are looking for]
- Background in data science, computer science, ML, AI, statistics, or related quantitative field.
- Strong statistical thinking, experimentation and evaluation skills.
- Experience building and evaluating ML/AI models, and applying techniques such as prediction, optimisation, text analysis or similar methods to real-world problems.
- Strong Python skills for data analysis and model development, with experience using common data science, ML libraries, and AI frameworks.
- Able to frame problems clearly, communicate to, and work across diverse stakeholders, including business, engineering, and architecture teams.
- Good interpersonal skills and experience working with vendors or external partners, including the ability to review and challenge technical solution design.
- Strong sense of ownership, intellectual curiosity, and divinely dissatisfied.
- Working knowledge of airport management and air traffic management will be a plus.
Note: Your appointment designation will commensurate with your relevant work experience. Successful candidates will be offered a 3-year contract in the first instance and may be considered for placement on a permanent tenure or subsequent contract renewal.
