Senior Product Data Scientist

About Amplify Health

Who We Are

Amplify Health Asia Pte. Limited (Amplify Health) is a pan-Asian health technology and analytics company which brings together health technology assets, proprietary data analytics and healthcare expertise to support innovation across the healthcare value chain.

Headquartered in Singapore, Amplify Health operates in 10 markets across the region: Australia, Hong Kong, India, Indonesia, Malaysia, New Zealand, the Philippines, Singapore, Thailand and Vietnam.

Amplify Health develops integrated solutions that empower healthcare payors, providers and policymakers across Asia to identify value and drive new partnerships, understand variation and address systemic inefficiencies—with the aim of improving outcomes for individuals and the sustainability of health systems.

Powered by a clinically enriched data foundation, Amplify Health’s health intelligence platform combines modular AI solutions, context-aware automation and deep regional insights to offer localised, AI-powered health solutions spanning health payment integrity to chronic disease management. The company’s technology has earned recognition at several industry competitions, including the Celent Model Insurer Awards, ITC Asia Awards and SBR Technology Excellence Awards.

As an ISO27001 certified organization, Amplify Health maintains clearly defined policies, structured oversight mechanisms and ongoing risk assessments that ensure alignment with global best practices on enterprise data security

Our Vision and Ambition

To build the leading healthcare AI and platform services company in Asia that transforms the delivery of health and wellness for patients and communities by combining and leveraging the distinctive and complementary assets and strengths of AIA and Discovery.

Amplify Health will simplify access to health data and AI Innovation to accelerate distinct and disruptive healthcare value insights and resulting improvements in health outcomes through value-based care, personalised care plans and aligning individuals’ lifestyle/ behavioural choices.

By 2028, Amplify Health will have in place one of Asia’s strongest health-tech and AI capabilities; a comprehensive, integrated health technology stack supported by precision insights derived from proprietary data pools.

The Position

Summary

The Senior Product Scientist will serve as a recognized organisational expert in Generative AI, Agentic AI, NLP and healthcare AI systems. This role shapes the Data & AI technical strategy and architecture, leads complex and high-impact AI initiatives, and establishes reusable, responsible AI capabilities across products, markets and business functions.

The ideal candidate combines exceptional depth in NLP, LLMs, RAG and agentic systems with broad architectural, data, analytics, product and healthcare domain judgement. The candidate defines how reliable AI systems should be designed, evaluated, governed and scaled, while developing the technical community through mentorship, standards and thought leadership.

Responsibilities

• Own the full model lifecycle for assigned models within one product: data assessment, EDA, feature engineering, experimentation, validation, deployment, monitoring, recalibration and retirement.
• Build reusable, configurable models across ML, NLP and GenAI, deployable to any customer through configuration and pre-designed extension points, never customer-specific code.
• Develop and productionise GenAI/ LLM-based workflows where relevant, including prompting, retrieval, fine-tuning approaches and evaluation harnesses.
• Apply advanced methods appropriate to the problem: predictive modelling, forecasting, causal inference, survival analysis, uplift, optimisation, anomaly detection and NLP.
• Establish robust evaluation designs, including out-of-time and out-of-population validation, leakage controls, calibration, explainability, fairness, uncertainty and model-risk assessment.
• Produce the model documentation, implementation playbooks and evaluation evidence that ship with the release, so implementation teams can deploy without you.
• Provide independent validation of models built by other teams, never of models you built yourself.
• Partner with engineering on reusable features, model pipelines, scoring services and monitoring capabilities.
• Deliver ad-hoc analysis and insight, define and validate the product's metrics, and lead dashboards that track adoption and realised value across customers
• Champion approved AI-assisted development tools to accelerate design, analysis, testing and documentation, with appropriate governance over confidentiality, reproducibility and review.
• Mentor junior data scientists, conduct technical reviews and raise standards for analytical rigour, code quality and delivery discipline

Candidate Profile

Required Qualifications

• 6+ years developing and implementing end-to-end machine learning or AI solutions, with production deployments at scale.
• Deep expertise in statistics, machine learning, feature engineering, evaluation and interpretation, with demonstrated experience in several advanced methods.
• Hands-on experience with NLP and transformer-based models, and practical exposure to LLM workflows, fine-tuning, evaluation and RAG.
• Strong proficiency in Python, SQL, PySpark, Databricks, MLflow, PyTorch, Azure AI services and LLM APIs.
• Proven record of building reusable models or components that deploy across multiple customers or markets without rebuilds.
• Strong grounding in evaluation rigour: leakage controls, out-of-time validation, calibration, explainability, fairness and model risk.
• Experience leading complex technical workstreams and mentoring data scientists; 2+ years is highly desirable.
• Experience driving adoption of AI-powered development tools for design specs, model cards, experiment summaries and runbooks, with measurable productivity gains.
• Excellent written and verbal communication, including explaining technical concepts to non-technical stakeholders.
• Demonstrated ability to work in a fast-paced matrix environment, managing stakeholder expectations, priorities and timelines

Preferred Qualifications

• Experience in healthcare, health insurance, payer or provider analytics, population health, claims, care management, clinical operations or health data platforms.
• Experience with healthcare data standards, privacy requirements, regulated environments and responsible AI considerations.
• Hands-on experience with Azure, Databricks or equivalent cloud and data platforms.
• Working knowledge of MLOps and LLMOps, CI/CD for ML, feature stores, model registries and monitoring.
• Experience optimising systems for accuracy, latency, reliability, cost and maintainability.
• Exposure to multimodal AI, knowledge graphs, medical text analytics or clinical decision support.

What Good Looks Like

• Models you build deploy to a new customer through configuration, not a rebuild.
• Evaluation is rigorous enough that results survive contact with customer data.
• Documentation and playbooks are complete enough that customer implementation teams do not need you.
• High ownership mindset with a focus on outcomes, not just models.
• Raises the standard of those around you through review and mentorship.

Join Us

If you are passionate about leveraging data to drive healthier outcomes across Asia and thrive in a dynamic, mission-driven environment, we encourage you to apply.

Amplify Health is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.