The Protegé – Machine Learning will support AI and data‑driven initiatives within the Travel Claims department by assisting in the development, enhancement, and maintenance of machine learning solutions. The role aims to strengthen internal AI capabilities, improve operational efficiency, and support the department's digital transformation agenda.
Job Description
1) Machine Learning & AI Support
- Assist in developing and enhancing machine learning models for travel claims use cases such as claims categorization, document classification, OCR, NLP, and basic anomaly detection.
- Support model training, testing, validation, and performance evaluation under guidance from senior team members.
- Perform data preparation, cleansing, labelling, and feature engineering to support AI model development.
2) Operational & Project Support
- Support AI proof‑of‑concept (POC), UAT activities, and production rollout.
- Assist in monitoring model performance and identifying opportunities for improvement or retraining.
- Support investigation and troubleshooting of AI‑related issues impacting claims processing.
3) Documentation & Knowledge Management
- Maintain proper documentation of AI models, workflows, datasets, and processes.
- Assist in preparing technical and operational documentation for internal stakeholders.
- Support knowledge transfer activities to ensure continuity and sustainability.
4) Collaboration & Continuous Improvement
- Work closely with Operations Technology, business users, IT teams, and vendors.
- Participate in agile ceremonies, project discussions, and enhancement initiatives.
- Keep up‑to‑date with basic AI/ML trends and tools relevant to insurance and claims processing.
Qualification / Requirement
- A Bachelor's Degree in: Computer Science, Data Science / Artificial Intelligence, Software Engineering, Statistics / Applied Mathematics, Information Technology or related fields.
- Basic understanding of machine learning concepts: Classification, regression, clustering, Model training vs inference, Familiarity with Python for data analysis or ML tasks, Exposure to tools such as: Jupyter Notebook, pandas, NumPy, scikit‑learn (basic usage)
- Technically inclined with strong fundamentals in data and machine learning
- Keen to apply AI concepts in real operational business use cases
- Comfortable learning through hands‑on, guided, and incremental delivery
- Interested in long‑term growth within digital transformation, analytics, or AI roles
Nice‑to‑Have Exposure (Not Mandatory)
- OCR, NLP, or document processing projects
- Basic understanding of APIs or system integrations
- Exposure to cloud platforms or AutoML tools
- Knowledge of SQL or data querying
