Director, Pharmacovigilance Quality Oversight AI Lead

5 days ago

New York, New York, United States Pfizer Full time
Pharmacovigilance AI Quality Oversight Lead

ROLE SUMMARY

The Pharmacovigilance AI Quality Oversight Lead is responsible for overseeing the strategic development and implementation of quality plans, establishing guidelines, and managing oversight governance to ensure the quality and reliability of AI systems that may affect pharmacovigilance.

This involves contributing to and participating in various quality oversight activities/committees established to drive discussion and action related to mitigating risks to the pharmacovigilance system from the use of artificial intelligence.

ROLE RESPONSIBILITIES

  1. Develop and implement a comprehensive quality oversight strategy for AI systems, ensuring alignment with organizational objectives, regulatory requirements, and industry best practices.
  2. Establish guidelines, policies, and procedures for quality assurance in AI, including data validation, model validation, performance testing, and scalability testing.
  3. Collaborate with cross-functional teams, including data scientists, software engineers, BPOs/SMEs, and legal/compliance teams, to define quality requirements, standards, and metrics for AI projects.
  4. Oversee the development of quality plans for AI initiatives, ensuring they are comprehensive, effective, and aligned with project goals.
  5. Manage oversight governance committees to ensure compliance with quality standards and regulatory requirements, and facilitate effective decision-making and risk management.
  6. Conduct regular assessments of AI projects to assess compliance with quality standards, identify gaps and areas for improvement, and provide recommendations for corrective actions.
  7. Collaborate with internal stakeholders and external partners to ensure alignment and adherence to quality guidelines and standards.
  8. Stay up-to-date with the latest advancements and trends in AI technologies, quality assurance methodologies, and regulatory requirements, and apply this knowledge to drive continuous improvement in quality oversight practices.
  9. Provide guidance and support to project teams on quality assurance best practices, tools, and methodologies, ensuring consistent and effective implementation across AI projects.
  10. Foster a culture of quality and compliance within the organization, promoting awareness and understanding of quality standards and requirements.
  11. Assume a lead role in ensuring inspection readiness on behalf of SQ, including inspection risks whose origins are outside of Safety.
  12. Collaborate with Head of PVQO to influence key external regulators regarding Pfizer's continuous quality improvement activities in the safety and risk management arena and interfaces with regulators, industry groups, and other key external stakeholders, as appropriate.
  13. Develop effective collaboration with other quality functions, linking with key stakeholders across Business Units or Partner Lines, as well as external industry and professional organizations.
  14. Provide a leadership role and act as the Subject Matter Expert (SME) on quality and compliance metrics, regulations, process improvements, technology, or specific work processes for the use of AI within the pharmacovigilance system.
  15. Provide strategic leadership to the delivery of PVQO services, policies, and works across stakeholder groups in collaboration with Head of PVQO.
  16. Provide strategic oversight for the development of quality policies and strategies for customer outputs across sites and customer groups.
  17. Ensure PVQO services are available across sites and customer groups to ensure needs and deliverables for the processes and products are met and promote continuous improvement.
  18. In conjunction with Head of PVQO, promote cross-group consistency, standards, and strategies across WWS and other partners.
  19. In conjunction with Head of PVQO, foster harmonization across sites, customers, and processes for the integrated delivery of PVQO services; champion, maintain, and instill a global perspective with a focus on strategy, promoting quality oversight and 'Right First Time' initiatives.
  20. With the Head of PVQO, ensure a global understanding of the PVQO vision and its connection to the RDM Quality Management System in support of Business Units and other Partner Lines; foster effective relationships with key internal/external customers and stakeholders.
  21. Lead virtual teams for process and project-related activities.
  22. Mentor and coach key PVQO staff as identified by succession plans.

TECHNICAL SKILLSETS NEEDED

Comprehensive knowledge of current regulations and guidelines for governing the use of artificial intelligence and its impact on pharmacovigilance.

Knowledge and experience in database system design, implementation, upgrade, or migration.

Technical Expertise – Applies technical and line knowledge of key concepts in own discipline and may act as a key technical resource within the line.

Proficient with software commonly used to present and analyze data (Word, PowerPoint, and Excel) required. Knowledge of Python and other programming languages will be an asset.

QUALIFICATIONS

BS Degree (or equivalent) in computer science, engineering, or a related field.

An advanced degree is desired, and in general, candidates for this job would have a degree in a science or technology-related discipline and extensive experience within the pharmaceutical industry.

Minimum 7-10 years in quality assurance, with a focus on technologies and systems within the pharmaceutical industry.

Strong understanding of AI concepts, algorithms, and frameworks, such as deep learning, neural networks, reinforcement learning, etc.

In-depth knowledge of quality assurance methodologies, tools, and best practices, with a track record of successfully implementing them in AI projects.

Experience in developing quality plans and guidelines for AI initiatives, ensuring compliance with regulatory requirements.

Familiarity with regulatory frameworks and standards related to AI, such as GDPR, HIPAA, ISO 27001, etc., and pharmacovigilance regulations.

Excellent analytical and problem-solving skills, with the ability to identify risks, gaps, and areas for improvement in AI systems.

Strong leadership and project management skills, with the ability to effectively manage oversight governance committees and drive quality initiatives.

Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.

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