Senior Data Scientist (AI & NLP)

Job Title: Senior Data Scientist (AI & NLP) Company: Amplify Health Job Category: Machine Learning Roles & Responsibilities: Amplify Health is Asia’s leading health technology and analytics organisation, providing our customers with integrated solutions to make healthcare more accessible, affordable and effective across the region. 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. 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. We are hiring a Senior/ Lead Data Scientist to serve as a recognised 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 * Translate ambiguous business and healthcare problems into structured AI solutions with clear measurement frameworks, success metrics and delivery pathways. * Define the enterprise technical strategy, reference architectures and capability roadmap for NLP, Generative AI, retrieval\-augmented generation, multimodal AI and agentic systems. * Act as the senior technical authority for high\-risk and high\-impact AI systems; make architecture trade\-offs across model selection, prompting, fine\-tuning, retrieval, tool use, memory, orchestration, latency, cost, security and maintainability. * Lead technical due diligence for foundation models, embedding models, vector stores, orchestration frameworks and vendors, including build\-versus\-buy and model\-risk decisions. * Lead the design of production\-grade AI systems where LLMs, RAG, NLP and agents are core runtime components of the delivered solution, not merely development aids. * Define patterns for agent planning, tool use, permissions, state and memory, observability, fallback mechanisms, human\-in\-the\-loop controls and safe failure handling. * Shape reusable AI platforms, knowledge services, evaluation harnesses, guardrails and LLMOps capabilities in partnership with engineering, technology, cybersecurity, risk and product leaders. * Clearly distinguish development\-process automation from runtime AI\-system behaviour: govern coding and analysis assistants as productivity tools while separately engineering and validating RAG, LLM and agentic components that operate within delivered AI systems. * Establish rigorous evaluation frameworks covering task quality, groundedness, retrieval performance, hallucination risk, safety, robustness, bias, privacy, latency, cost and human oversight. * Define governance standards for AI system design, validation, monitoring, model risk, human accountability, auditability and responsible AI practices. * Ensure AI systems are designed with appropriate controls for healthcare privacy, security, compliance, explainability, fairness and operational safety. AI\-Assisted Development and Productivity * Champion the responsible adoption of modern AI\-powered development tools, such as coding assistants, analytical copilots and platform\-native AI assistants, to streamline model development, automate repetitive tasks, accelerate analytical insights and improve engineering productivity. * Define approved usage patterns, quality controls, adoption metrics and value measures for AI\-assisted development and process automation. * Ensure productivity tools are adopted responsibly without compromising security, intellectual property, scientific quality or decision accountability. * Influence executive strategy, investment and risk decisions by communicating evidence, uncertainty, trade\-offs, expected impact and operational implications. * Build organisational capability through mentorship, standards, training, communities of practice and external thought leadership. * Develop senior technical talent and raise the overall quality of AI system design, scientific reasoning and production delivery across the function. Work Location: Chennai, Tamil Nadu, India Availability: Full time

Required Qualifications Preferred Qualifications Key Skills: Machine Learning, Python, PyTorch, NLP Salary: Not disclosed