Statistical Programming Innovation Lead

Overview

In this role you will elevate Ipsen’s Biometry into an AI-enabled, automation-first function. You will lead a cross-disciplinary team to deliver ML, LLM-driven analyses, and automated data applications across R&D. You’ll partner with IT, Digital/Analytics, and external providers to turn high-value use cases into governed, scalable solutions. You drive adoption and ensure robust, validated, reproducible outputs that accelerate decision-making. This is a chance to shape a capable AI-native Biometry. You will work closely with study teams and leadership to deliver tangible impact.

Responsibilities

• Lead the AI-Programming capability within Biometry, defining strategy, roadmap, standards and operating model for AI-enabled programming, automation, application development and information science.
• Build and lead a specialist team of clinical data scientists, AI-programming experts and application developers, including workforce planning, capability development, coaching, prioritization, delivery oversight and succession planning.
• Drive automation capabilities to improve speed, quality, consistency and scalability of Biometry deliverables and workflows.
• Scale ML, LLM and AI-enabled analytics to support priority clinical, statistical, programming and R&D decision-making use cases.
• Design and deliver fit-for-purpose applications, tools and data products that make Biometry insights accessible and reusable.
• Establish governance for AI-enabled programming covering intake, validation, documentation, version control, access, model monitoring and training.
• Collaborate with Statistical Programming, Biostatistics, Clinical Development, Data Management, IT, Digital/Data/Analytics/AI and external providers to transform high-value use cases into governed, scalable solutions.
• Evaluate external tools, vendors and platforms, with buy-vs-build decisions based on value, feasibility, compliance, security, scalability and maintainability.
• Promote adoption through training, communities of practice, reusable playbooks and demonstrations of value across priority studies.

Key requirements

• 10+ years in pharmaceutical/biotech/technology/data science or statistical programming with significant leadership experience.
• Strong understanding of clinical trials, data science, and clinical data flow, validation and outputs.
• Proven track record in developing or scaling automation, applications, data products or AI-enabled programming in regulated environments.
• Proficiency in modern programming and AI/ML tools (R, Python, SAS or equivalent), ML, LLMs, GenAI, data governance.
• Experience leading technical teams and delivery portfolios, including resourcing, coaching and change adoption.
• Ability to communicate complex trade-offs and business value to senior stakeholders.
• Experience with clinical data standards, metadata management, validated computing environments, cloud platforms and version control.

• accountability
• talent development and coaching
• clear, structured communication
• R
• Python
• SAS

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