Director - Pharmacometrics AI Lead (Remote or Hybrid)

Job Description

The Quantitative Pharmacology and Pharmacometrics (QP2) department drives model-informed drug discovery and development (MIDD) to routinely enable efficient drug discovery/development and/or regulatory decisions. The Pharmacometrics group within QP2 brings an experienced leadership team, deep modeling expertise and state-of-the-art modeling approaches across multiple therapeutic areas and modalities to drive portfolio impact from discovery through life-cycle management. The team is externally visible and continues to be at the leading edge of building innovative state-of-the-art tools together with applying AI/ML techniques to drive pipeline impact. As we enter a new era of AI-driven drug development, our mission is to amplify MIDD through cutting-edge AI, advanced analytics, and automation. With AI/ML now integral to decision-making at our Company, this role gives the Director the opportunity to shape pipeline impact and lead a talented team of pharmacometricians.

We are seeking a visionary Pharmacometrics AI Lead to shape and execute on a bold, multi-year transformation agenda within QP2. This Director will work with the Pharmacometrics Head to frame and deliver on the integration of artificial intelligence, machine learning, and digital technologies into quantitative pharmacology workflows—positioning our Company at the forefront of AI-enabled drug development.  A strong core foundation in standard Pharmacometric Approaches (e.g., PK/PD, disease progression modeling, MBMA) is essential, alongside the ability to translate emerging AI/ML capabilities into practical, high-impact applications within clinical development and regulatory contexts. This Director will shape next-generation MIDD approaches, accelerate decision-making across the portfolio, and unlock new value through data, automation, and predictive analytics.

Key Responsibilities:

• Identify high-value, scalable use cases that can innovate and accelerate development timelines and execute on the strategic integration of AI/ML into QP2 pharmacometric approaches to advance MIDD across the portfolio

• Evaluate emerging AI/ML technologies, lead proof-of-concept initiatives, and translate successful pilots into enterprise-scale solutions that deliver real-world value

• The incumbent will participate in our Company's key Enterprise-wide AI/ML efforts as a departmental liaison on such workstreams in partnership with IT, our Company Enterprise Strategy Office, and other Partner functions to implement robust AI solutions

• Will take a leadership role in influencing and driving a longer-term departmental strategy for utilization of AI/ML in Pharmacometrics

• Collaborate with QP2 TA Representatives and Pharmacometricians to identify opportunities for AI/ML usage in MIDD on our Company Programs

• Lead adoption initiatives through training programs and upskilling efforts, fostering a culture of innovation and empowering teams to embrace AI/ML methodologies

• Initiate and manage external collaborations which include technology providers, academia, and consortia to develop new AI/ML methodologies and lead our external outreach to the scientific pharmacometrics community

• Maintain a current understanding of emerging AI/ML technologies/vendors and lead assessments for application to Pharmacometric workflows

• Take a leading role in developing Agentic AI workflows that drive efficiencies in standard pharmacometric workflows

Required Experience:

• Ph.D. with at least 8 years of experience where “experience” means having a record of increasing responsibility and independence in a similar role in pharmaceutical drug development

• Educational background in pharmacometrics, mathematics, or statistics/biostatistics or a related quantitative discipline

• Deep hands-on expertise in pharmacometrics (e.g., population PK and PK/PD analyses, model-based meta-analysis, dose-response and exposure-response analyses, disease modeling, trial simulation, optimal study designs, strategic decision analyses)

• Demonstrated leadership in applying AI/ML methods in drug development with at least 2 years of demonstrated examples (through publications or other) of utilizing AI/ML/NLP approaches for drug development.

• Proven success in scaling digital solutions from pilot to enterprise deployment

• Deep knowledge of drug development, pharmacokinetics and pharmacology, MIDD principles, regulatory expectations, and the evolving role of AI/ML in clinical development