Data Scientist Submission Data and Content Generation & Reuse (AIDCG) - Pharma R&D
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Job Description
Structured overview of role & requirementsAbout This Role
Lead end-to-end development and deployment of data-driven AI/ML models for clinical data and regulatory submission assets.
Build advanced generative AI agents and bespoke multi-agent workflows (e.g., LangGraph, GraphRAG) to support clinical data scientists in a GxP regulated environment.
Drive medium-sized projects that align with business strategy and significantly influence clinical data quality and authoring timelines.
Minimum Requirements
Proven experience independently owning data science projects from inception to deployment, influencing medium-sized business decisions.
Proficiency in Python (AI/ML backend/agent logic) and R (clinical statistical programming), familiarity with SAS is a plus.
Hands-on expertise with LangChain, LangGraph, AWS AgentCore, and advanced RAG methodologies including chunking, embeddings, GraphRAG.
Ability to communicate complex analytical findings clearly to technical and non-technical stakeholders.
Ideal Candidate Profile
Experienced in regulated GxP clinical or pharmaceutical R&D data environments with strong domain and technical expertise in advanced generative AI and multi-agent architectures.
Technically versatile with mastery over multiple programming languages, AI/ML frameworks, and advanced data visualization/statistical modeling.
Capable of independently driving medium-sized strategic analytical projects that improve clinical data content management and regulatory submission processes.