Associate Director Biostatistics - -AI/Biostat (Remote)

AI/ML Engineering: 3+ years developing and deploying AI/ML solutions, including LLMs, RAG pipelines, or MLOps, with strong Python skills and exposure to clinical or life sciences data. Experience in one of the following areas: Biostatistics: 5+ years (PhD) or 7+ years (Master’s) in pharmaceutical biostatistics, with strong SAS/R skills, Python familiarity, and exposure to AI/ML tools.

Contact: Sabrina Garcia -

teamnt@penfieldsearch.com

Associate Director, Biostatistics & AI
Location: Remote – USA (Occasional Travel)

Position Overview

We are seeking an Associate Director, Biostatistics & AI to support clinical development through advanced statistical analysis and the implementation of AI/ML solutions within biometrics. This role combines pharmaceutical biostatistics with applied AI technology to improve efficiency, data quality, and regulatory compliance.

Key Responsibilities

• Lead statistical analysis and reporting for Phase II–IV clinical trials, including adaptive designs, Bayesian methods, and regulatory submissions.
• Support NDA, BLA, and MAA submissions and responses to regulatory authorities.
• Design, implement, and validate AI/ML tools that integrate with SAS, R, Python, and clinical data systems.
• Develop AI-driven solutions for statistical analysis plans (SAPs), TFL automation, data validation, and regulatory documentation.
• Establish AI governance, validation, and monitoring processes in compliance with GxP and applicable regulatory requirements.
• Collaborate with Clinical Development, Regulatory Affairs, Medical Affairs, and other cross-functional teams.
• Oversee CRO statisticians and programmers and contribute to SOPs and best practices.

Qualifications

• PhD or Master’s degree in Biostatistics, Statistics, Computer Science, AI, Data Science, or related field.
• Experience in one of the following areas:
• • Biostatistics: 5+ years (PhD) or 7+ years (Master’s) in pharmaceutical biostatistics, with strong SAS/R skills, Python familiarity, and exposure to AI/ML tools.
  • AI/ML Engineering: 3+ years developing and deploying AI/ML solutions, including LLMs, RAG pipelines, or MLOps, with strong Python skills and exposure to clinical or life sciences data.
• Knowledge of clinical trial methodology, regulatory requirements (FDA, EMA, ICH), and applicable data standards.
• Familiarity with CDISC standards, GxP environments, and regulatory submission processes.
• Strong communication, problem-solving, and cross-functional collaboration skills.
• Demonstrated initiative in developing and implementing AI-powered solutions.