Applied AI Associate (Public Health)

About the Company

Our client is a leading public health organisation working closely with government institutions to design, implement, and scale high-impact health programmes across India. They are seeking a senior leader to head their Health Analytics and AI function, driving the application of advanced analytics and AI across large-scale digital health and health protection programmes. The ideal candidate will bring strong Data Science and AI expertise, experience leading technical teams and large technology transformations, and the ability to translate complex policy and operational challenges into actionable, decision-grade insights.

Roles and Responsibilities

• Translate the programme priorities into clear technical requirements and work closely with specialised Data Science and AI teams on larger builds.
• Support the preparation and structuring of data required for analytics and insights generation.
• Build scalable, monitored, and reproducible data pipelines and analytical tooling for production use.
• Develop AI-assisted workflows for data structuring, validation, and quality improvement, including clinician-in-the-loop mechanisms.
• Build de-identification, anonymisation, synthetic data, and augmentation pipelines aligned with health data privacy and governance requirements.
• Support the development of natural-language querying capabilities, enabling NHA and state teams to interact with aggregated programme data.
• Establish strong model monitoring, drift detection, evaluation, and reproducibility practices, including benchmark datasets and task-specific performance metrics.

Skills and qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Public Health, or a related field.
• 5+ years of experience building ML/AI systems from prototype through production, including deployment, monitoring, versioning, and maintenance.
• Strong experience evaluating and benchmarking LLM-based systems, including evaluation datasets, performance thresholds, and regression testing.
• Hands-on experience building RAG systems, including embeddings, vector stores, and natural-language data querying.
• Experience with anonymisation, de-identification, and ideally synthetic-data generation.
• Strong understanding of large-scale data processing, batch and incremental pipelines, and query/cost optimisation.
• Working knowledge of the public-health domain, with strong proficiency in Python, SQL, and mainstream ML frameworks.

What's On Offer

• Opportunity to apply cutting-edge AI/ML to large-scale public health programmes, working with complex, real-world healthcare data.
• Build production-grade AI solutions from the ground up, spanning RAG, LLM evaluation, data pipelines, anonymisation, synthetic data, and responsible AI.
• Work at the intersection of AI, technology, and public health, with the opportunity to build solutions that can influence healthcare delivery and outcomes at scale