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Open nowPosted 7 days ago

Product Analytics Manager

MyCareersFuture94,028 open roles

Pay
SGD 6,000 – SGD 7,500 a month
Where
Singapore
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Your applicationOpen nowProduct Analytics ManagerMyCareersFuture · Singapore

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The clock on this job

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Share of postings closed within
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  2. 3.3%3 days
  3. 7.7%7 days
  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 7 days ago

The posting

Role Overview

We are seeking a detail-oriented and execution-focused Product Analytics Manager to support the delivery, measurement, and continuous improvement of our digital products and platforms. This role sits at the intersection of product execution, engineering, and analytics, ensuring that roadmap priorities are delivered efficiently and that product and marketing decisions are grounded in data.

The Product Analytics Manager will work closely with engineering as the day-to-day product partner, translating product strategy into build-ready requirements, supporting sprint execution, and ensuring high-quality releases. In parallel, the role will be responsible for setting up and maintaining product analytics foundations—events, dashboards, and performance reporting—to provide actionable insights across the marketing funnel and product features.

This role is critical in enabling faster execution, stronger product quality, and data-informed decision-making across product, marketing, and partnership teams.

Key Responsibilities Sprint Execution & Delivery Management

  • Own sprint planning, backlog grooming, sprint reviews, and retrospectives.
  • Translate product roadmap priorities into clear, actionable user stories with well-defined acceptance criteria.
  • Ensure sprint commitments are realistic, well-prioritised, and aligned with business goals.

Engineering Partnership

  • Act as the primary day-to-day product partner for engineering teams.
  • Unblock developers by clarifying requirements, resolving dependencies, and coordinating inputs across teams.
  • Proactively identify and escalate risks, trade-offs, and scope changes early to stakeholders.

Product Specifications & Documentation

  • Draft, maintain, and continuously refine execution-level PRDs and functional specifications for prioritised features.
  • Define edge cases, error states, and operational workflows to ensure smooth development and downstream operations.
  • Ensure documentation remains up to date throughout the development lifecycle.

Product Analytics & Insights

  • Support the setup and maintenance of product analytics instrumentation, including event tracking and funnels.
  • Build and manage dashboards to track product feature performance, user behaviour, and marketing funnel effectiveness.
  • Provide basic analysis and insights to inform product optimisation, marketing performance, and partnership decisions.

Release Management & Quality Assurance

  • Coordinate UAT activities and ensure release readiness across teams.
  • Validate acceptance criteria and ensure features meet quality standards prior to production launch.
  • Support post-release monitoring to identify issues and opportunities for improvement.

Cross-functional Coordination

  • Work closely with design, operations, content, marketing, and partnerships teams to ensure timely inputs and alignment.
  • Facilitate smooth handoffs between teams to maintain delivery velocity and product quality.

What This Role Should Achieve (Success Outcomes)

Within the first 6–12 months, the Product Analytics Manager should:

  • Enable predictable and efficient sprint execution with minimal carryover or rework.
  • Improve product delivery quality through clear requirements, thorough acceptance criteria, and disciplined release processes.
  • Establish a reliable product analytics foundation, including key events, funnels, and dashboards.
  • Provide actionable insights that directly influence product improvements, marketing optimisation, and partnership strategies.
  • Strengthen collaboration between product, engineering, and cross-functional teams, reducing blockers and misalignment.
  • Help the organisation make faster, more confident product decisions based on data rather than assumptions.

Success Metrics

  • On-time sprint delivery and reduced scope changes mid-sprint.
  • Reduction in post-release defects or rework.
  • Adoption and usage of product analytics dashboards by product, marketing, and partnership teams.
  • Clear linkage between analytics insights and product or marketing improvements.
  • Positive feedback from engineering and cross-functional stakeholders on clarity, execution, and collaboration.
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