POSTING

Position: POSTING ONLY
Associate Director, Biostatistics & AI - Remote

Our client is an established biotech whose latest need is for an Associate Director, Biostatistics & AI to combine pharmaceutical statistical expertise with artificial intelligence and machine learning (AI/ML) to improve clinical development workflows. This role will support clinical trial design, statistical analysis, regulatory submissions, and the development of AI-powered tools that automate processes, improve data quality, and increase efficiency. You will also help ensure AI solutions meet applicable pharmaceutical quality, compliance, and regulatory requirements.

* Please Note:

We welcome candidates from either a pharmaceutical biostatistics background with applied AI experience or an AI/ML engineering background with exposure to clinical or life sciences data.

Key Responsibilities

• Support statistical design, analysis, and reporting for Phase II–IV clinical trials and regulatory submissions.
• Develop and implement AI-powered tools to automate statistical programming, reporting, data quality checks, and regulatory documentation.
• Build, test, validate, and monitor AI/ML solutions in a GxP-compliant environment.
• Ensure AI tools follow applicable regulatory, documentation, and governance requirements.
• Collaborate with Clinical Development, Regulatory Affairs, Medical Affairs, Pharmacovigilance, IT, and external vendors.
• Oversee CRO statisticians and programmers on assigned programs.
• Develop SOPs and best practices for statistical analysis, programming, and AI implementation.

Qualifications

Candidates should hold a PhD or Master’s degree in Biostatistics, Statistics, Computer Science, AI, Data Science, or a related field and meet the requirements of one of the following pathways
.

Pathway A:
Biostatistics-Focused

• 5+ years of pharmaceutical biostatistics experience with a PhD, or 7+ years with a Master’s degree.
• Advanced SAS and/or R skills, with working knowledge of Python.
• Experience with clinical trials, CDISC standards, and regulatory submissions.
• Exposure to AI/ML tools and a strong interest in expanding AI capabilities.

Pathway B: AI/ML-Focused

• 3+ years of hands‑on AI/ML engineering experience.
• Strong Python skills and experience with LLMs, RAG pipelines, AI workflows, or MLOps.
• Exposure to clinical or life sciences data and familiarity with statistical concepts.
• Working knowledge of SAS and/or R and an interest in pharmaceutical development.

All Candidates

• Strong communication, collaboration, and problem-solving skills.
• Understanding of applicable statistical and regulatory principles relevant to their background.
• A proactive approach to building and implementing AI-powered solutions in a regulated environment.