Associate Director

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. Requirements 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. #J-18808-Ljbffr