Summary

The Global Head of Statistical Programming (SP) is globally responsible for driving consistency and building capabilities across TAs and maximize value realization of automation and standardization for programming across AQS. They are leader in driving functional excellence in programming in AQS. They have significant experience and expertise in the drug development process, regulatory activities, key statistical reporting, with an excellent track record of operational, organizational and technical leadership. They are externally engaged and recognized as a thought leader in modern statistical programming; they define and drive adoption of good programming practices in AQS.

About the Role

Global Head Statistical Programming

• Drive and build statistical programming quality, consistency, validation, automation and continuous learning across all AQS.
• Proactively monitor quality of programming for AQS deliverables. Collaborate with Technology and Scientific Computing to define and implement modern processes and tools that measure and drive quality. When quality issues or near misses are detected, ensure robust CAPA defined and implemented.
• Engage with internal and external partners to define and drive modern implementation of SDTM, ADaM and reporting standards. Partner with CDO and Clinical to define standards, with Technology and Scientific Computing to leverage modern technology to automate implementation. Proactively work with project teams where new standards are needed and collaborate externally to ensure Novartis is engaged in defining/automating new standards and is an early adopter.
• Collaborate with Data Management in developing tools and processes particularly related to data standards, cleaning and processing emerging data types and defining/maintaining metadata standards.
• Build modern programming capabilities across AQS including open source, R. Collaborate closely with Technology and Scientific Computing to develop and deliver training across AQS. Provide just-in-time help for project teams.
• Develop and lead specialized data wrangler/engineers enabling scalable use of new data types
• Lead, influence, collaborate and proactively shape the external environment including data standards, regulatory guidelines, industry practices and professional organizations
• Identify internal and external drivers and opportunities to define and implement cross-functional strategies to maximize productivity and efficiency through use of effective processes and tools, global corporate standards and utilization of strategic alliances with external partners.
• Build and develop team with expertise in programming, clinical domain, data analysis, machine learning and AI knowledge, software engineering and business acumen.

• University degree in Life Science, Computer Science, Engineering or another relevant field.
• Vast experience of involvement in life sciences, clinical research or drug development in a global/matrix environment in pharmaceutical industry
• Significant experience, and proven ability to effectively engage, manage and influence associates from widely varying backgrounds & functions within a dispersed and highly matrixed organization.
• Experience with requirements for data science and analytics tools (e.g., Python, R, SAS), iterative development methodologies (eg: Agile) and artificial intelligence and machine learning applications in clinical or research settings.
• Thorough knowledge of GxP, industry data and metadata standards, QA and regulatory/clinical development process.
• Coach/lead and manage people: inspire and empower others to be strong leaders.
• Strong interpersonal skills for bridging scientific, technical and business stakeholders.
• Track-record of ideating and executing organizational change projects.
• Demonstrated ability to establish strong internal and external partnership with key stakeholders.
• Ability to work, gain trust and influence at all levels of the organization.
• Excellent interpersonal and communication skills (written and verbal).
• Analytical, process-oriented and data driven mind-set
• Track record of success in leading cross-functional teams.
• Proven ability to manage and coach people.
• Fluency in English (spoken & written)