Senior Scientist, Data Science, GenAI

What you'll do

• Develop, test, and deploy AI solutions for documentation, knowledge retrieval, and decision support within the TDS ecosystem.
• Build and test components of agentic AI workflows to coordinate models, tools, and data across supply chain processes.
• Implement reusable AI capabilities using established DDSAI architectures and platform standards.
• Translate stakeholder needs into technical AI requirements for regulated environments.
• Apply evaluation frameworks to assess LLM systems for traceability, robustness, uncertainty, and usability.
• Follow responsible AI practices including human-in-the-loop validation, risk assessment, and content safety governance.
• Apply software engineering practices such as modular design, testing, and lifecycle management to all code.
• Communicate implementation progress, system limitations, and risks to both technical and non-technical stakeholders.

What we're looking for

• Degree in Engineering, Data Science, Life Sciences, Computer Science, or related field.
• Advanced degree preferred.
• 1–3 years of hands-on experience developing AI, NLP, or machine learning solutions, including practical experience applying large language models (LLMs).
• Working knowledge of Pharmaceutical Product Development, including Chemistry, Manufacturing and Controls (CMC).
• Proficiency in Python, with experience developing, testing, and documenting code.
• Strong communication skills, with the ability to explain technical topics to non-technical stakeholders.
• Exposure to open-source agentic frameworks (e.g., LangGraph, DSPy, mem0) (preferred).
• Familiarity with retrieval-augmented generation, embeddings, vector databases, and model evaluation (preferred).