Job Responsibilities
Advanced Analytics & AI Development
- Apply Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI) techniques to solve real-world insurance challenges across underwriting, pricing, claims, and customer experience.
- Execute the full modeling lifecycle: data integration, model selection, validation, deployment, and client engagement.
Generative AI Innovation
- Explore and implement GenAI use cases such as underwriting automation, claims optimization, and agentic workflows for summarization, inference, and information retrieval.
- Combine traditional predictive analytics with GenAI to enhance efficiency and unlock new business value.
Project Management & Collaboration
- Lead and participate in analytics projects across Asia-Pacific, Middle East, and Africa.
- Work closely with actuaries, underwriters, IT teams, and global analytics centers to deliver impactful solutions.
- Present analytics findings and solutions to internal and external stakeholders.
Continuous Improvement & Knowledge Sharing
- Support business units with advanced research methods and provide specialized know-how in AI and analytics.
- Develop and implement solutions to improve operational efficiency and business performance.
- Conduct training and share best practices within the analytics community.
Job Requirements
- Master's or Ph.D. in Data Science, AI, Statistics, Applied Mathematics, Computer Science, Engineering, or related field (preferred).
- Minimum 2 years of industry experience in data science, AI, or ML.
- Hands-on experience in Python (front-end, back-end, API integrations); full-stack development and JavaScript visualization are advantages.
- Strong theoretical knowledge of GenAI, ML, and DL.
- Familiarity with RESTful APIs, microservices, and LLM applications.
- Experience with GenAI workflows (summarization, inference, information retrieval) is a plus.
- Demonstrable projects on Kaggle, GitHub, or analytics blogs are an advantage.
- Insurance/reinsurance experience, especially in claims automation, is desirable.
- Proficiency in Python and related libraries for ML/DL.
- Understanding of SDLC and model deployment processes.
- Knowledge of big data technologies and cloud platforms is a plus.
- Strong stakeholder management and ability to explain technical concepts to non-technical audiences.
- Excellent documentation and presentation skills.
- Innovative mindset, ability to work under tight timelines, and willingness to travel within Asia.
