Associate Director IT Global Data Analytics, Innovation&Digital Experimentation

Company:  Avanos Medical
Location: Alpharetta
Closing Date: 21/10/2026
Salary: $180,000 - $220,000 Per Annum
Hours: Full Time
Type: Permanent

Job Description

Avanos Medical seeks an Associate Director IT Global Data Analytics, Innovation & Digital Experimentation to lead data strategy across our global medtech business. In this role, you will define and deliver advanced analytics, AI/ML, and data engineering solutions that optimize clinical, commercial, and operational decisions. You will own the data experimentation roadmap, partner with business and clinical leaders to identify high value use cases, and oversee end to end project delivery. Responsibilities include managing a technical team, governing data platforms, ensuring data quality, and championing innovation while maintaining security, privacy, and regulatory compliance in a patient-focused environment.

Responsibilities

  • Lead global data analytics and digital experimentation strategy for Avanos Medical
  • Identify, prioritize, and deliver high-value analytics and AI/ML use cases across business functions
  • Oversee design and implementation of data platforms, pipelines, and governance frameworks
  • Manage and mentor a technical team of data engineers, scientists, and analysts
  • Ensure data quality, integrity, security, and regulatory compliance in a healthcare context
  • Partner with clinical, commercial, and operations leaders to translate needs into technical solutions
  • Drive experimentation frameworks (A/B testing, pilots, POCs) to validate data-driven initiatives
  • Report performance, insights, and ROI of analytics programs to senior leadership
  • Collaborate with IT and cybersecurity to maintain resilient, scalable data infrastructure
  • Champion a culture of innovation, continuous improvement, and patient-focused decision-making

Required Skills

  • Data analytics strategy
  • Data engineering (ETL/ELT, data pipelines)
  • Cloud data platforms (AWS, Azure, or GCP)
  • SQL and relational databases
  • Python or R for analytics and data science
  • Machine learning and AI concepts
  • BI and data visualization tools (Tableau, Power BI, etc.)
  • A/B testing and experimentation frameworks
  • Data governance, security, and privacy (including healthcare context)
  • Project and stakeholder management
  • Statistical analysis and modeling
  • Data architecture and warehousing
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