Associate Director, AI​/Data Science

Responsibilities

• Define and lead analytics and AI strategy using modern methodologies, including LLMs, GenAI applications, agentic workflows, and RAG-based solutions.
• Research, test, and implement new technologies, data sources, and AI/ML approaches for pharmacovigilance, regulatory submissions, quality, and clinical data insights.
• Establish AI governance, validation protocols, and responsible AI practices aligned with GxP and regulatory requirements.
• Collaborate with cross‑functional R&D analytics groups to advance standards, innovation, and analytics governance.
• Present findings, model evaluations, and business impact of AI‑enabled solutions to technical and non‑technical stakeholders.
• Mentor and upskill junior staff in data science, GenAI, LLMs, prompt engineering, RAG architectures, and responsible AI practices.

• Bachelor’s degree required; master’s degree preferred in computer science, mathematics, statistics, computational biology, or a related field.
• 7+ years of experience in a biotechnology or pharmaceutical organization using data to support R&D decision‑making.
• Expert programming skills with Python, R, LLMs, or other languages applied to large, complex, and disparate data sources.
• Experience developing LLM applications, prompt engineering, RAG pipelines, fine‑tuning approaches, and AI solutions for regulated life sciences settings.
• Knowledge of pharmacovigilance, regulatory information management, quality systems, clinical trial data, and compliance frameworks.