Data Product Manager
Singapore - Technology Centre
PART OF A ENERGETIC AND DYNAMIC CITO GROUP
Based in SG as part of a global technology community, you will work within multi-disciplinary agile squads working alongside agile leaders, data specialists, data scientists, automation engineers, cloud engineers, and business specialists. The CITO group is tasked with ensuring engineering excellence as a basic standard for the delivery of Dyson Solutions, Services and Products.
WHO YOU ARE
You think and dream all things data and automation, enjoy working as part of an energetic and focused team that solves problems that have a direct line of sight to business value. You are consumed with automating anything that does not represent business value. You have a sense of ownership and enjoy hands-on technical work. Your values are important to us in the way you live and work.
WHAT YOU'LL DO
As a Product Manager, you will work in multi-disciplinary agile squads delivering AI-enabled products and services.
- Manage product delivery including managing resources, expectations, and risks; be responsible for ensuring user stories are delivered against business priorities.
- Lead the end-to-end product development lifecycle, from ideation to launch. Working closely with engineering and data science teams to operationalize machine learning models into products.
- Develop and articulate a clear product vision and strategy for AI products. Define user stories and acceptance criteria from business opportunities into product features.
- Define key performance indicators (KPIs) for AI products and analyse product metrics to iterate and enhance AI capabilities.
- Actively measure business value to support justifications on current and future product investment.
- Achieve collaboration with stakeholders to encourage transparency and alignment of business priorities, dependencies, and constraints.
- Instill continuous improvement and change behaviour mindsets using Lean and Design Thinking practices, drawing on other resources where appropriate.
- Stay abreast of industry trends, market dynamics, and emerging technologies to inform product decisions.
- Flexible in thinking and result oriented!
BASIC QUALIFICATIONS
- 7+ years of experience in product planning and product design in AI products, data analytics, or business intelligence
- Must have experience working with AI technologies including machine learning, natural language processing, and computer vision
- Hands on experience with advanced Python and ETL tools for data transformation and analysis
- Familiar with process improvement practices and business process management
- Experience in managing backlog, developing user stories, and estimating story points
- Experience in developing business cases and managing investment budgets with ability to drive new value proposition and influence business to embrace new innovations
- Proven track record securing investments from senior executives through product pitching
- Demonstrated ability to build trust and engage at C-levels
- Ability to think strategically but also dive deep into details and drive execution
- Demonstrated leadership working in cross-functional technical teams (direct/virtual)
- Strong technical and business acumen to draw insights and make product trade-off
- Experience working in an Agile, SCRUM or Lean Start-up environment
- MBA or PhD 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Business Intelligence Computer Vision Data Analytics Engineering ETL KPIs Machine Learning ML models NLP PhD Python Scrum
Perks/benefits: Career development Flex hours Startup environment Transparency
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