Statistical Analyst - AI & Automation Enablement

Purpose
Support the transformation of Statistical Programming & Analysis (SPA) into a strategic analytics partner by enabling initiatives that enhance analytical insight, automation, and operational efficiency.

Act as the bridge between SPA product teams and scalable digital and AI execution, translating analytical, regulatory, and operational needs into industrialized AI-, automation-, and tool-based solutions in close collaboration with internal and external stakeholders.

This role enables SPA to move from pilots to platforms, turning prototypes and MVPs into standardized, reusable, and compliant capabilities that scale across studies, programs, and products.

Key Responsibilities

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  Embed with SPA product teams to understand analytical workflows, regulatory constraints, and decision-critical use cases

  
  


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  Translate SPA needs into clear technical requirements for AI, automation, and digital solutions

  
  


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  Act as the primary interface between SPA and engineering teams across Data Science & AI and IT

  
  


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  Industrialize AI models and automation workflows into scalable, reusable capabilities

  
  


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  Drive a “build once, scale many times” approach to analytics, automation, and tools

  
  


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  Redesign SPA workflows from an AI-first and platform-oriented perspective

  
  


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  Ensure solutions meet regulatory expectations for compliance, auditability, and data integrity

  
  


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  Enable the transition from pilots to governed, repeatable capabilities while reducing complexity

  
  

Qualifications

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  Degree in Statistics, Data Science, Computer Science, Engineering, or a related field

  
  


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  Proven experience at the intersection of analytics, AI/ML, automation, or digital platforms

  
  


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  Ability to collaborate credibly with statisticians, programmers, and clinical stakeholders without owning study delivery

  
  


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  Experience translating complex, domain-specific problems into scalable technical solutions

  
  


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  Comfort working at the intersection of regulated science and modern engineering practices

  
  


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  Strong stakeholder management and influencing skills across technical and non-technical audiences

  
  


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  Proactive, solution-oriented mindset with the ability to move from concept to industrialized output