 ##  [Lead Data Scientist, Gen-AI Expert](/req-10085342-lead-data-scientist-gen-ai-expert "Lead Data Scientist, Gen-AI Expert") 

  Job ID REQ-10085342 

 

 Aug 13, 2026 

 

 LOC_CN 

 

 

 

###  About the Role 

Key Responsibilities：

• Responsible for translating business pain points related to commercialization, medical affairs, and life sciences into clear machine learning or generative AI technical pathways, product requirements, and mid- to long-term capability roadmaps.

• Deeply engage in commercialization, medical affairs, and life sciences business scenarios; work with business teams to clarify high-value questions; rapidly translate ambiguous needs into executable AI/ML technical solutions; and achieve end-to-end delivery through prototype development, PoC, business validation, and production deployment.

• Lead the development of enterprise-level knowledge bases, retrieval-augmented generation (RAG), intelligent search, memory systems, and reusable data pipelines, covering knowledge architecture design, document processing and indexing strategies, metadata and access management, data asset reuse, evaluation set development, quality monitoring, content governance, and continuous operation mechanisms.

• Responsible for algorithm prototype design, performance optimization, model evaluation, and capability iteration for generative AI applications. Apply technologies including large language models, prompt engineering, knowledge graphs, recommendation systems, causal inference, deep learning, or multi-agent frameworks, and make engineering trade-offs across accuracy, latency, cost, traceability, and user experience to form stable, scalable, and traceable enterprise-level solutions.

• Establish enterprise-level AI engineering and standardization frameworks, including model evaluation metric systems, fine-tuning processes, deployment and monitoring standards, quality tracking, risk control, and compliance assessment approaches, ensuring that AI capabilities operate safely, compliantly, and reliably in pharmaceutical industry scenarios.

• Work closely with business, data, engineering, IT, compliance, legal, and external vendor teams to manage cross-functional expectations and delivery cadence; clearly communicate technical value, business impact, and return on investment (ROI) to senior stakeholders; and drive the adoption of AI culture and standardized workflows on the business side.

Essential Requirements:

• Master’s degree or above, preferably in computer science, artificial intelligence, machine learning, data science, statistics, mathematics, information management, or related disciplines; experience in healthcare, life sciences, pharmaceutical commercialization, consulting, or enterprise-level digital transformation is preferred.

• More than 5 years of experience in artificial intelligence, machine learning, generative AI, data science, enterprise-level AI products, or platform engineering; full project experience from algorithm prototyping, performance optimization, and engineering deployment to continuous iteration is preferred.

• Solid capabilities in frontier algorithms and models, with familiarity in large language model (LLM) applications and fine-tuning methods, including supervised fine-tuning (SFT), reinforcement learning (RL/RLHF), prompt engineering, and multi-agent collaboration frameworks, as well as an understanding of cross-disciplinary technologies such as knowledge graphs, recommendation systems, causal inference, deep learning, and multimodal AI.

• Production-grade AI engineering and standardization capabilities, with familiarity in model evaluation metrics, fine-tuning processes, data pipelines, knowledge base and memory system design, deployment monitoring, quality governance, traceability management, and stability requirements for production systems.

• Excellent business understanding and technical translation capabilities, with the ability to decompose complex business problems into executable functional requirements, data requirements, and system solutions; balance technical investment, business value, cost efficiency, and return on investment (ROI); and integrate internal and external data resources and partner ecosystems.

• Excellent cross-functional project management, communication, and senior stakeholder influencing skills, with the ability to coordinate business, data, engineering, compliance, legal, and vendor teams; establish standardized processes in complex environments; drive the adoption of AI culture; and continuously enhance the team’s innovation capabilities.



 

###  Role Requirements 

 

**Why Novartis:** Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? [https://www.novartis.com/about/strategy/people-and-culture](https://www.novartis.com/about/strategy/people-and-culture "https://www.novartis.com/about/strategy/people-and-culture")

**Benefits and Rewards:** Learn about all the ways we’ll help you thrive personally and professionally.  
[Read our handbook (PDF 30 MB)](https://www.novartis.com/sites/novartis_com/files/novartis-life-handbook.pdf)



 

 

 

 

 

 Division DIV_IM 

 

 Business Unit Sales 

 

 Location LOC_CN 

 

 Site Shanghai (Shanghai) 

 

 Company / Legal Entity CN06 (FCRS = CN006) Beijing Novartis Pharma Co., Ltd 

 

 Functional Area FCT_SA 

 

 Job Type Full time 

 

 Employment Type Regular 

 

 Shift Work No 

 

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 Job ID REQ-10085342 

 

 

###  Lead Data Scientist, Gen-AI Expert 

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