Health Data Scientist (Gen AI Agentic AI)

The Health Data Science Team in Singapore collaborates with multiple global teams to deliver critical capabilities in machine learning (ML), advanced analytics, disease modeling, and the development of data assets and infrastructure. The team specializes in building ML models using multimodal data sources, including structured data, free text, images, video, and audio, to power digital health solutions that facilitate real-world and clinical data capture. In addition, the team is responsible for developing and maintaining governed data platforms, pipelines, and assets that support large-scale real-world and clinical data analytics.

To support its growing portfolio, the team is seeking Health Data Scientists who will contribute to a diverse range of projects spanning multiple health and technological domains.

What will you be doing in this role?

In this role, you will collaborate with internal and external stakeholders globally on multiple initiatives involving digital health solutions, real-world evidence, and clinical data.

You will lead the development of GenAI and multimodal, multi-agent solutions leveraging text, image, audio, and video capabilities to support digital health tools. In addition, you will design interactive analytical frameworks for the governed analysis of real-world and clinical data, while establishing robust testing and monitoring processes to ensure the accuracy, reliability, and performance of generative and agentic systems.

You will also be responsible for effectively communicating insights, outcomes, and recommendations to a diverse range of stakeholders within Danone and across external partner organizations.

To be successful in this role you will need … 
Technical Skills & Experience
• Master’s or Ph.D. degree in a relevant technical discipline.
• Strong expertise in deep learning and proficiency with at least one leading deep learning framework.
• Experience developing and managing MLOps pipelines and end-to-end machine learning lifecycles.
• Hands-on experience with multimodal Generative AI technologies, including VAEs, GANs, diffusion models, Vision Transformers (ViT), Swin Transformers, large language models (BERT, GPT), fine-tuning techniques, LoRA, knowledge distillation, and vision-language models.
• Proven experience designing and implementing multi-agent systems, including memory architectures, vector databases, RAG, reasoning and planning agents, tool integration, MCP, agent orchestration frameworks, guardrails, reinforcement learning, and automated evaluation mechanisms.
o Experience with Agent Bricks is advantageous.
o Experience with Strands Agents is advantageous.
• Strong project management capabilities, including scope definition, resource planning, timeline management, and success measurement.
o Familiarity with Agile methodologies such as Scrum and Kanban is highly desirable.
• Experience working with cloud platforms, particularly AWS and/or Azure.
• At least 5 years of experience in Data Science within the healthcare, life sciences, or digital health sector.
Soft Skills
• Strong stakeholder management and collaboration capabilities across cross-functional and global teams.
• Ability to translate business challenges into actionable data science and AI initiatives.
• Excellent communication skills, with the ability to present complex scientific and technical concepts to non-technical audiences in a clear and compelling manner.