Analytics and AI Enablement Lead

Role Overview
As the owner of the end-to-end lifecycle of analytics and AI-powered products, you will guide them from market research and product vision through roadmap planning, development, launch, and iteration. Positioned at the crossroads of AI engineering, data science, design, and business strategy, you will translate complex technologies into user-focused solutions that deliver tangible results. You will align use cases to business strategy and work with Chubb's leadership team to ensure delivery aligned to business outcomes.

Key Responsibilities

• Product Strategy & Roadmapping
  Develop the vision and roadmap for analytics and AI-driven initiatives. Conduct market research to identify opportunities and align features with business and market needs.
• Cross-Functional Collaboration 
  Partner with engineering, ML/data science, underwriting, marketing, sales, and legal stakeholders to shape product requirements from concept to release.
• Governance 
  Aligning use cases to business strategy and clear business outcomes. Presenting and running business focussed prioritization and governance of incoming demand working with Chubb's executive leadership team. 
• Backlog & Execution Management
  Translate business objectives into actionable product backlog items. Prioritize tasks based on impact, feasibility, and user value. Manage agile delivery through sprints, MVPs, and beta launches.
• Market & User Research
  Perform ongoing market and competitive analysis, customer interviews, and user testing. Leverage insights to refine product direction.
• Performance Monitoring & Analytics
  Establish and track KPIs (e.g., adoption, retention, accuracy). Use data-driven insights to optimize and iterate on AI functionality.
• Ethics & Risk Management
  Ensure adherence to responsible AI practices by addressing bias, privacy, fairness, and regulatory concerns. Implement safeguards during model development and deployment.
• Go-to-Market & Stakeholder Enablement
  Support launch planning, marketing strategies, sales materials, training, and product evangelism. Keep stakeholders (executives, partners) informed of progress and impact.

Required Skills & Experience

• Technical Knowledge
  • Understanding of data science, AI/ML fundamentals, including algorithms, model training and evaluation, NLP/CV, and model validation.
• Product & Domain Expertise
  • 5–7+ years of experience in Product Management, ideally with AI/ML or data-driven products. Proven success in launching AI solutions.
  • Proficiency in agile methodologies (Scrum/Kanban) and backlog management.
• Analytical & Strategic Abilities
  • Skilled in analyzing data, extracting insights, and managing ML development to drive decisions based on metrics and user feedback.
  • Strong business acumen to position analytics and AI as a strategic solution to real-world problems, avoiding "AI for AI's sake."
• Soft Skills
  • Exceptional communication skills to bridge technical and non-technical stakeholders and craft clear PRDs/user stories.
  • Empathy and leadership to effectively manage diverse, cross-functional teams with clarity and alignment.
  • Adaptability and creativity to navigate the rapidly evolving analytics and AI landscape.

Required Skills & Experience

• Technical Knowledge
  • Understanding of data science, AI/ML fundamentals, including algorithms, model training and evaluation, NLP/CV, and model validation.
• Product & Domain Expertise
  • 5–7+ years of experience in Product Management, ideally with AI/ML or data-driven products. Proven success in launching AI solutions.
  • Proficiency in agile methodologies (Scrum/Kanban) and backlog management.
• Analytical & Strategic Abilities
  • Skilled in analyzing data, extracting insights, and managing ML development to drive decisions based on metrics and user feedback.
  • Strong business acumen to position analytics and AI as a strategic solution to real-world problems, avoiding "AI for AI's sake."
• Soft Skills
  • Exceptional communication skills to bridge technical and non-technical stakeholders and craft clear PRDs/user stories.
  • Empathy and leadership to effectively manage diverse, cross-functional teams with clarity and alignment.
  • Adaptability and creativity to navigate the rapidly evolving analytics and AI landscape.