Lead the lifecycle of analytics and AI products, aligning them with business strategy and managing cross-functional teams to deliver user-focused solutions.
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.
Top Skills
Agile
AI
Computer Vision
Data Science
Kanban
Machine Learning
Nlp
Scrum
Similar Jobs
Aerospace • Artificial Intelligence • Computer Vision • Software • Analytics • Defense • Big Data Analytics
The Integration Architect will lead technical engagements to integrate geospatial analytics into ISR platforms, ensuring successful customer adoption and deployment.
Top Skills:
CesiumGdalGeotiffGnssGrpcH.264H.265InsJetsonKlvMisbMpeg-TsNxpOpencvPyTorchRaspberry PiRestSfmSlamStanag 4609Unity
Fintech • Mobile • Payments • Software • Financial Services
Lead the QA strategy for the AML domain, manage a QA team, ensure compliance with AML regulations, and drive continuous improvement.
Top Skills:
AI
Fintech • Mobile • Payments • Software • Financial Services
The role involves defining and expanding Wise's asset management product, focusing on user experience and technical foundations, while collaborating across teams.
Top Skills:
JavaKafkaSpring Boot
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.
