GenAI Data Scientist

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.