Data Architecture Lead

2 months ago

London, Greater London, United Kingdom Haleon Full time

About Haleon

Haleon is a world-leading consumer health company, shaping the future of everyday health for billions of people. Our unique combination of deep human understanding and trusted science drives innovation in our global portfolio of category-leading brands.

About the Role

We are seeking a motivated and experienced Senior AI/ML Architect to join our Data Architecture and Platforms team. As a key member of the Data Office, you will design, build, and manage Haleon's enterprise-wide AI/ML architecture, aligning it with our data strategy and driving continuous improvement in our capabilities and efficiencies.

Responsibilities

  • Translate business and machine learning engineer requirements into scalable and efficient AI/ML solutions.
  • Ensure AI/ML solutions are strategically aligned with Haleon's goals, contributing to measurable business impact.
  • Lead in designing, building, and managing a comprehensive AI/ML architecture, maintaining end-to-end accountability.
  • Collaborate with the Principal AI/ML Architect to establish AI/ML architecture frameworks and design standards.
  • Engage with various business functions, regions, tech partners, and architects to support and drive AI/ML initiatives across Haleon.
  • Focus on enhancing AI/ML capabilities and efficiencies, keeping abreast of latest trends and technologies in the field.
  • Collaborate with Data Architects, Tech Solution Architects, and Enterprise Architects to ensure the enterprise view of AI/ML is represented accurately within an application or solution scope.

Qualifications

  • Bachelor's or Master's degree in Computer Science with a total experience of 5-8 years.
  • Proven track record in AI/ML architecture, with substantial experience in data architecture and modeling.
  • Strong proficiency in AI/ML technologies and tools, with the ability to integrate them into scalable solutions.
  • Excellent communication abilities, with a talent for bridging the gap between technical and non-technical stakeholders.
  • Ability to align AI/ML solutions with broader business strategies and adapt to evolving organizational needs.
  • Demonstrated success in working collaboratively across different functions and cultural boundaries within an organization.

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