Data Scientist

• Provide data-driven insights, dashboards, and scenario modeling to support demand and supply planners, S&OE/S&OP processes, and enterprise decision-making
• Drive continuous improvement in analytics, data quality, and model reliability
• Drive automation and advanced analytics, leveraging Python, SQL, and BI tools to scale insights
• Partner with more senior team members to align analytics with standards, governance, and process maturity efforts
• Generate dashboards and KPIs that support IBP governance and forum discussions
• Enable S&OE/S&OP with near-term supply-demand coverage analytics, including early warning indicators

Data Scientist, Integrated Business Planning

• Partner with stakeholders to clarify business questions into ML problem statements (classification, ranking, uplift, forecasting, optimization, GenAI RAG/agentic workflows, etc.).
• Write and maintain an ML System Design Spec: problem hypothesis, decision loop, users, constraints, acceptable risk, SLAs/SLOs, and post-deployment guardrails.
• Conduct advanced exploratory data analysis on large datasets using Python, pyspark, SQL, and visualization libraries.
• Design, implement, and validate machine learning and statistical models to address complex healthcare and insurance challenges.
• Collaborate with DevOps engineers to productionize models using containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines.
• Build and maintain reusable ML accelerators that standardize feature engineering, model training, and evaluation across tasks.
• Facilitate technical workshops and presentations to ensure clarity and buy-in across diverse audiences.
• Advocate for responsible AI by incorporating fairness, explainability, and bias detection into model development.

Senior Data Scientist

• Work with data like images, videos, audio, and text etc.
• Design, train, optimize, and deploy deep learning models with GPU.
• Develop comprehensive unit tests and documentation, and rigorously evaluate and benchmark model performance and quality.
• Communicate effectively between the business team and the engineering team to gather and implement project requirements.
• Own the end-to-end process, from defining the technical problem to deploying the solution in collaboration with engineers.
• Stay current with the latest advancements in deep learning and AI technologies.

Data Scientist – Computer Vision, AI

• Partner with business stakeholders to identify high-impact opportunities to deploy AI/ML across the insurance value chain
• Define and execute Asia data, analytics, and AI strategy aligned with business priorities
• Act as a strategic advisor to senior leadership on data and AI transformation
• Translate complex data and AI concepts into clear business value narratives
• Translate business problems into data and AI solutions with measurable impact
• Oversee the design, development and implementation of advanced analytics and AI across underwriting, claims, distribution and operations domains
• Oversee scalable data platforms supporting analytics and AI workloads
• Ensure data readiness for AI/ ML/GenAI (structured and unstructured data pipelines)
• Partner with Technology and Security to ensure safe, compliant AI adoption
• Drive a culture of data-driven and AI-augmented decision-making
• Enforce Data Management Policy and AI Governance Policy along with the respective standards to improve data quality and ensure responsible use of AI across the organisation
• Build, lead, and develop a high‑performing, multi‑disciplinary D&A team across Asia

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Data Scientist, Integrated Business Planning

Senior Data Scientist

Data Scientist – Computer Vision, AI

Head of Data and Analytics