Senior Data Scientist - Clinical AI development

Senior Data Scientist - Clinical AI development

Facility: Data & AI

Location:Lexington, MA, US

About the Department

Our Research & Development organization brings together the best minds in life science innovation. The teams located in facilities in Lexington, Watertown, Cambridge and Plainsboro reflect the full R&D continuum, from early research through late-stage clinical development. Here, we are building for the future, creating a distinct R&D community based on collaboration, partnerships, and cutting-edge research across multiple modalities and therapeutic areas.

We recognize that improving human health starts here and that patients rely on us. Our R&D hub merges biotech speed and agility with large pharmaceutical company quality, resources, and stability, uniting the best of both worlds to develop new medicines for patients.

The Position The Senior Data Scientist II will contribute to the research team's effort towards exploring and creating new technology and being a world leader in data science within our fields.

The Senior Data

Scientist II will bring elements of data collection, preparation, and engineering as well as software engineering in a data science context.

The Senior Data

Scientist II will develop and validate algorithms and models in support of data science efforts with a high degree of initiative and self-sufficiency. Moreover, the Senior Data Scientist II will guide more junior Data Scientists in the execution of their tasks, as well as supports them in networking in a complex global organization.

Open to hiring at the Lead level commensurate with experience

Relationships The Senior Data Scientist II reports to the Associate Director of the Clinical AI development area. Internal partners include fellow Data Scientists, AI Engineers, and System Architects who serve as primary day-to-day collaborators in the design and delivery of AI/ML solutions. The role also works closely with medical professionals, clinical trial squad members, and biostatisticians to ensure that solutions are grounded in clinical context and meets the needs of drug development workflows

Essential Functions

• Scientific work:
• Develop and validate LLM-based solutions for content retrieval, generation, summarization and inference applied to healthcare and drug development challenges
• Enable & assist in software engineering for AI products: architect services, design APIs, build backend systems, and integrate with frontend applications while meeting performance, safety, privacy & ethics requirements.
• Build and maintain requisite data solutions , including vector databases, embedding pipelines, and knowledge bases to support retrieval-augmented generation (RAG) and document understanding
• Collaborate with other data scientists to design, code, train, test, deploy, and iterate on machine learning systems
• Explore model-driven reasoning through the application of prompt engineering, model fine-tuning techniques (supervised, LoRA,PEFT, etc.), and optimization methods (quantization, distillation, caching) as part of day-to-day development work.
• Create technical documentation, runbooks, and training materials for model usage and maintenance.
• Accomplishes objectives with a high degree of self sufficiency
• Collaborate with other Data Scientists, as well as engineers from other disciplines to complete daily tasks
• Actively participates in cross-functional teams to develop AI and ML solutions
• Stay current on GenAI/LLM research, best practices and technology roadmap
• Achieves business goals, shares learnings, knowledge and skills and promotes cross-functional teamwork.
• Raise the level of competency in the team by seeking and sharing domain knowledge in the area of Data Science, as well as Novo Nordisk’s therapy areas

Physical Requirements

UP to 10% overnight travel required.

Qualifications

• Master’s degree or PhD highly preferred. Minimum of Bachelor’s degree required. Degree within subject matter expertise preferred
• Master’s Degree with 4+ years’ relevant experience, or PhD with 2+ years’ relevant experience, or a Bachelor’s degree with 6+ years’ relevant experience can be considered
• Relevant experience includes:
• Experience working in LLM and generative AI domain: model selection, system design, fine-tuning (supervised, LoRA, PEFT, etc.), prompt engineering, evaluation, observation, etc.
• A foundational understanding of deep/reinforcement learning models and architectures such as transformers, GANs, VAEs, etc.
• Experience in designing agentic solutions to tackle problems in healthcare, with conside