Pharmaceutical Sciences, Technology & Innovation Lead (Sr. Director)

Objectives/Purpose

This is a senior scientific, strategic, and technology leadership role within Pharmaceutical Sciences (PharmSci), R&D, accountable for shaping and advancing an integrated PharmSci technology and innovation strategy with particular emphasis on AI/ML, computational, and in silico-first approaches for CMC applications.

The role identifies, prioritizes, and accelerates opportunities where advanced analytics, predictive modeling, AI/ML, and digital capabilities can improve CMC decision-making, development speed, robustness, scalability, and lifecycle outcomes across PharmSci.

The role serves as a key PharmSci ambassador for external collaborations and strategic partnerships, representing PharmSci’s data, digital, and AI/ML priorities in joint steering committees, alliance governance forums, and scientific partnership engagements.

Accountabilities

Define and maintain the integrated PharmSci technology and innovation strategy, with specific focus on AI/ML, data-driven, and in silico-first capabilities that enable CMC advancement across development, industrialization, manufacturing readiness, and lifecycle management.

Identify and prioritize high-value use cases where AI/ML, predictive modeling, simulation, and computational approaches can improve CMC outcomes, including speed, robustness, control strategy, process understanding, risk reduction, and right-first-time execution.

Serve as a senior scientific and strategic leader connecting CMC domain needs with digital, data science, and computational capabilities to ensure that innovation investments are grounded in practical business value and lifecycle applicability.

Act as a primary PharmSci representative and ambassador in external collaborations, alliances, and partnership governance, including participation in joint steering committee (JSC) and related forums focused on data/digital, AI/ML, and in silico innovation.

Build, manage, and grow a strong external ecosystem across biotech partners, technology companies, academia, consortia, and other collaborators to expand PharmSci access to emerging computational, AI/ML, and digital capabilities relevant to CMC.

Translate external partnership opportunities into actionable internal strategies, pilots, and capabilities by connecting external innovation with PharmSci priorities, scientific needs, governance requirements, and implementation pathways.

Partner across PharmSci technical functions, DD&T, data science, and other enterprise enabling teams to ensure AI/ML and digital solutions are scalable, compliant, sustainable, and aligned to enterprise architecture and operating models.

Provide leadership for the evaluation, piloting, adoption, and scaling of digital and computational capabilities, ensuring they are supported by appropriate governance, data foundations, change management, and measurable value realization.

Ensure that AI/ML and in silico-first approaches are applied with appropriate scientific rigor, CMC context, and regulatory/compliance awareness, supporting inspection readiness, lifecycle robustness, and operational feasibility.

Drive performance management across the technology and innovation portfolio by defining success metrics, monitoring value realization, and communicating progress, risks, and opportunities to senior stakeholders.

Core Elements Related to this Role

• AI/ML and in silico-first leadership in CMC
• External ambassador and partnership leadership
• Strong CMC credibility
• Bridge between science and digital innovation

Technical/Functional (Line) Expertise

• Strong end-to-end understanding of the CMC lifecycle, spanning development, scale-up, tech transfer, manufacturing, quality, and regulatory implications.
• Deep expertise in the application of AI/ML, advanced analytics, modelling, simulation, and/or in silico approaches to scientific or CMC-related problems.
• Strong understanding of how digital, data, and computational capabilities can be translated into practical CMC use cases and scalable business value in a regulated environment.
• Strong computational fluency, including familiarity with modern AI/ML methods, model development and deployment considerations, and the data requirements needed to enable successful use in practice.
• Ability to evaluate emerging AI/ML and computational technologies critically, including their scientific fit, maturity, scalability, and potential value for PharmSci.
• Strong understanding of CMC technology strategy and the interplay between scientific innovation, data foundations, digital platforms, implementation pathways, and lifecycle readiness.

Leadership

• Sets direction and aligns senior stakeholders around a coherent technology and innovation agenda with strong emphasis on AI/ML and in silico-first capability building for CMC.
• Demonstrates credible leadership across scientific, computational, technical, and strategic environments.
• Lets across influence networks, connecting PharmSci, enterprise enablers, and external collaborators around shared priorities and high-impact opportunities.
• Represents PharmSci with credibility in both internal and external forums, including senior governance and partnership settings.
• Drives change through vision, prioritization, communication, and adoption support.

Interaction

• Extensive engagement with PharmSci functional leaders, DD&T, data science, quality/compliance, regulatory, manufacturing, procurement/external partnerships, and finance.
• Serves as a key interface between PharmSci and external collaborators focused on AI/ML, digital, computational science, and CMC-relevant innovation.
• Represents PharmSci in selected internal and external governance forums, including alliance and joint steering committee structures where appropriate.

Innovation

• Applies a structured approach to identifying and advancing AI/ML and in silico opportunities that are scientifically meaningful, operationally feasible, and aligned to business priorities.
• Evaluates and shapes external innovation opportunities in partnership with collaborators and internal stakeholders.
• Promotes adoption of new computational approaches, digital capabilities, and ways of working that improve CMC performance and decision quality.

Dimensions and Aspects

• Technical/Functional (Line) Expertise
• Leadership
• Interaction
• Innovation

Education, Behavioural Competencies and Skills

• Mandatory: strong CMC background with deep understanding of end-to-end lifecycle considerations from development through manufacturing, quality, and regulatory.
• Mandatory: demonstrated expertise in applying AI/ML, computational, modeling, simulation, and/or in silico approaches to scientific, technical, or CMC-relevant problems.
• Mandatory: demonstrated ability to identify, shape, and translate data/digital or AI/ML opportunities into practical solutions with measurable business and scientific value.
• Mandatory: proven ability to represent an organization effectively in external collaborations, alliance governance, and/or joint steering committee environments.
• Mandatory: strong ability to bridge technical and scientific communities, including CMC experts, data scientists, digital teams, and external collaborators.
• Strong computational literacy and fluency with current AI/ML concepts, methods, and emerging technology trends, including ability to assess applicability and limitations in regulated environments.
• Demonstrated senior leadership experience in complex matrix organizations with strong stakeholder management, prioritization, and influence skills.
• Proven ability to build and sustain external partnership networks across industry, academia, and technology ecosystems.
• Strong business case framing and decision-making skills across value, risk, feasibility, compliance, readiness, and long-term scalability.
• Demonstrated change leadership and experience supporting adoption of new capabilities, tools, and ways of working at scale.