Senior Product Manager
New
S
Spotted ZebraHR Tech SaaS
United KingdomFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- AgileArtificial IntelligenceData AnalysisProduct ManagementStakeholder managementSaaS
Requirements
- Proven experience managing complex web-based SaaS products in fast-paced startup or scale-up environments
- Excellent prioritisation skills, balancing user needs, commercial priorities, technical feasibility, and delivery constraints
- Strong execution and delivery skills, with experience shipping impactful products at pace
- Comfortable operating hands-on within delivery-focused product roles
- Strong technical fluency and confidence working closely with engineering teams
- Ability to gather, refine, and communicate clear product requirements
- Experience collaborating closely with engineers and designers in lean, cross-functional teams
- Strong analytical skills, using quantitative and qualitative insights
- Comfortable creating wireframes, user flows, and lightweight UX concepts
- Experience leveraging AI tools and workflows
Responsibilities
- Own a key product area, working closely with the Head of Product to balance strategic direction with effective day-to-day execution
- Develop a strong understanding of user needs through a combination of qualitative research, stakeholder collaboration, and data analysis
- Drive product delivery from discovery through to launch, ensuring initiatives move forward efficiently and blockers are proactively resolved
- Work closely with Engineering and Commercial to translate user, business, and operational needs into clear, deliverable requirements
- Own and prioritise the product backlog, balancing new functionality, experience improvements, technical constraints, and platform enhancements
- Collaborate proactively across Product, Engineering, Design, Data Science, Operations, and commercial teams to align priorities and drive delivery
- Make pragmatic product decisions quickly, balancing user value, technical feasibility, business priorities, and delivery pace
- Stay close to implementation details and support teams throughout the delivery lifecycle, not just at the planning stage
- Identify clear success metrics and use data to evaluate product performance and inform prioritisation
- Leverage AI to accelerate discovery and delivery
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