Role Overview
Data Product Managers determine and oversee delivery of the strategy and roadmap for data-driven assets, products and solutions to achieve business outcomes and financial objectives. Their responsibilities include collaborating with technical and functional stakeholders to set priorities, managing delivery and operations, and providing direction and oversight to delivery teams. This role demands strong analytical mindset, bias for action and passion for building impactful data products in a dynamic environment.
Key Responsibilities
- Develop a deep understanding of business goals and processes to inform delivery priorities and recommendations for improvements.
- Develop strong relationships and regularly communicate with business stakeholders to shape requirements and prioritize needs. Translating business requirements into actionable product and technical features.
- Define and execute product roadmaps that drive measurable business outcomes, including planning resource allocation and team skill requirements.
- Work closely with technical teams to ensure timely delivery of high-quality data products and solutions, resolving obstacles and trade-offs as required.
- Communicate delivery progress and results to stakeholders, focusing on how data and AI solutions meet their business goals.
- Advocate for best practices in AI/ML, data management, data governance, and user experience into data products and solutions.
- Monitor performance and reliability of data products, coordinating with Data Operations to resolve outages, bugs, and performance issues.
- Define and monitor post-launch metrics, performance and user adoption, iterating on solutions to maximize sustained business impact.
- Drive change management, including training and supporting end users as AI workflows and analytics are integrated into their daily operations.
- Ensure alignment and adherence to corporate, financial and IT standards (e.g., architecture, privacy, compliance, security).
- Continuously track and evaluate emerging data/AI technology, industry trends, and best practices to drive innovation and inform product execution.
Competencies
- Proficient with Agile methodologies and tools (e.g., Jira, Confluence). Experience writing clear product requirements, user stories, and acceptance criteria with the help of AI.
- Skilled in prioritizing features and managing backlogs based on business value and technical dependencies. Demonstrated effective collaboration with cross-functional teams (engineering, analytics, business, etc.).
- Strong understanding of data platforms, data modelling and analytics/reporting tools.
- Good understanding of AI architecture, evaluation testing and context engineering.
- Demonstrated ability to synthesize complex technical specifications into clear, actionable insights for non-technical stakeholders across both written and verbal communication.
- Demonstrated strong business acumen and partnership with senior stakeholders. Building buy-in, influencing stakeholders and keeping diverse teams aligned.
- Excellent problem-solving, critical-thinking, and organizational skills. Ability to thrive in ambiguous, fast-paced environments.
- Ownership mindset with a bias for action and accountability for delivering measurable results.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, or related STEM field.
- Minimum 7 years experience in product or technical project management related to AI, data analytics, data management, or business intelligence.
- Proficient in SQL and knowledge of data processing, architecture and modern data platforms.
- Working experience with Data Science applications and AI/ML workflows.
- Industry experiences relevant to Dyson (eg. manufacturing, engineering) is highly desirable.
- Professional certification in Product or Project Management (e.g., AIPMM, CSPO, PMP) preferred.
Dyson is an equal opportunity employer. We know that great minds don't think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.
