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# Statistical Analyst - AI & Automation Enablement

- **Company:** Bayer SAS
- **Location:** Barcelona, Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Integrity, Web Platforms, Information Technology
- **Published:** September 24, 2026
- **Apply:** https://www.adzuna.es/contact-us.html

## About the Role

Degree in Statistics, Data Science, Computer Science, Engineering, or a related field
Proven experience at the intersection of analytics, AI/ML, automation, or digital platforms
Ability to collaborate credibly with statisticians, programmers, and clinical stakeholders without owning study delivery
Experience translating complex, domain-specific problems into scalable technical solutions
Comfort working at the intersection of regulated science and modern engineering practices
Strong stakeholder management and influencing skills across technical and non-technical audiences
Proactive, solution-oriented mindset with the ability to move from concept to industrialized output

## Description

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., Embed with SPA product teams to understand analytical workflows, regulatory constraints, and decision-critical use cases
Translate SPA needs into clear technical requirements for AI, automation, and digital solutions
Act as the primary interface between SPA and engineering teams across Data Science & AI and IT
Industrialize AI models and automation workflows into scalable, reusable capabilities
Drive a "build once, scale many times" approach to analytics, automation, and tools
Redesign SPA workflows from an AI-first and platform-oriented perspective
Ensure solutions meet regulatory expectations for compliance, auditability, and data integrity
Enable the transition from pilots to governed, repeatable capabilities while reducing complexity


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