Head of Statistical Programming (Oncology), Global Data Sciences, R&D, Orion Pharma
About this role
Job Description
We are seeking an experienced and visionary leader to establish and lead Orion's Statistical Programming function in Oncology.
The Head of Statistical Programming provides strategic, operational, and technical leadership for the Statistical Programming function within Global Data Sciences organization. This role is accountable for building and leading a high-performing global programming organization that delivers high-quality, regulatory-compliant programming outputs supporting clinical development, regulatory submissions, and evidence generation across the portfolio.
Reporting to the VP of Global Data Sciences, the Head of Statistical Programming is responsible for defining the Statistical Programming strategy, operating model, standards, and capabilities needed to support current and future development programs. The role partners closely with Biostatistics, Clinical Data Management, Clinical Development, Regulatory Affairs, Medical Writing, and external partners to ensure submission-ready programming deliverables are produced efficiently, consistently, and in compliance with global regulatory requirements.
The Head of Statistical Programming plays a key role in advancing innovation, automation, standardization, and AI-enabled programming capabilities while fostering a culture of quality, collaboration, continuous improvement, and inspection readiness.
Responsibilities
- Functional Leadership and Strategy
- Lead and develop the Statistical Programming function, including organizational design, talent strategy, workforce planning, and capability development.
- Define and execute the Statistical Programming vision, strategy, operating model, and roadmap aligned with Global Data Sciences and R&D objectives.
- Establish clear roles, responsibilities, governance, and accountability across internal teams and external partners.
- Portfolio and Delivery Oversight
- Provide oversight of programming activities across clinical studies and programs, e