⌘ Role Overview

Timeleft is looking for a senior full stack product data analyst to partner closely with Product and Leadership to turn data into strategic advantage. You’ll be the first product data analyst to join, so you’ll have a leading role in building out the craft the function. In addition, we are looking for someone who can actively contribute to our DBT data pipelines and data infrastructure.

This role sits at the intersection of product thinking, experimentation, and analytics. You will not only explain what happened and why, but proactively identify opportunities, shape hypotheses, and help design experiments that drive measurable impact.

You will help elevate our product analytics maturity from reactive reporting to structured, insight-led decision making.

⌘ Key Responsibilities

Product Partnership

• Act as a strategic partner to Product Managers and leadership, shaping discovery and roadmap priorities through data and insights.

Insight Generation

• Lead deep-dive analyses to identify user behaviors, friction points, and growth levers.
• Translate findings from “what happened” into clear, action-oriented recommendations.

Experimentation & Measurement

• Build out an experimentation practice that focuses on velocity and speed of learning
• Define clear success criteria, guardrails, and decision frameworks.

Analytics Infrastructure & Governance

• Contribute to the data model (DBT / BigQuery) to ensure reliable product metrics.
• Establish clear KPI definitions, documentation, and analytics best practices.

Storytelling & Influence

• Communicate insights with clear “so whats” tailored to senior stakeholders.
• Frame recommendations as testable bets and facilitate discussions around trade-offs and prioritization.

⌘ Expected Outcomes

Establish a coherent product KPI ecosystem: Define and operationalize a clear set of leading and lagging indicators, diagnostic metrics, and guardrails that span the full end-to-end user journey — ensuring alignment across Product, Growth, and Leadership.

Shift conversations from reporting to decision-making: Consistently elevate discussions from “what happened” to clear hypotheses, trade-offs, and recommended actions.

Increase experimentation velocity and decision quality: Improve both the speed of learning and the rigor of interpretation by strengthening experiment design, metric clarity, and post-test synthesis.

Surface high-impact opportunities on a recurring basis: Identify and articulate multiple product opportunities per quarter, framed as testable bets with expected impact and measurable outcomes.

Build durable institutional memory of product insights: Create structured documentation and synthesis mechanisms so that key learnings, experiment results, and behavioral insights are captured, searchable, and reused — reducing repeated analyses and preventing knowledge loss as teams evolve.

⌘ Skills & Competencies

Product Thinking

• Deep understanding of user funnels, activation, retention, and engagement
• Comfort discussing trade-offs between user value and business/revenue impact.
• Ability to think in terms of mechanisms and levers, not just metrics.
• Understanding and experience in design thinking methods and ways of working

Analytics and data skills

• Strong SQL skills and comfort working with event-driven datasets
• Solid understanding of experimentation, statistics, and causal inference
• Experience with cloud-based analytics (BigQuery preferred)
• Comfortable contributing to the data model through DBT
• Strong metric intuition — understands when numbers are signal or noise
• Experience working with product analytics tooling (Posthog preferred)

Ways of working

• Ability to synthesise complex findings and multiple data points (e.g. quant and qual) into clear narratives.
• Confident presenting to cross-functional and senior audiences.
• Comfortable pushing back constructively when needed
• Chooses the right tool for the right job
• Willingness to be flexible and deputise other roles when needed

⌘ Required experience

• 5+ years of experience in product analytics, data analysis, or related roles.
• Experience partnering closely with product teams.
• Demonstrated experience designing and analysing various experiments such as A/B tests, geo-tests and qualitative tests
• Experience working with event-driven product data.
• Strong knowledge of SQL and python
• Experience in consumer tech, marketplaces, or growth-oriented environments preferred.

⌘ What’s in it for you?

• A front-row seat in an exciting, fast-growing start-up.
• Employee stock options.
• The opportunity to develop your position and responsibilities as Timeleft grows.
• Take part in Timeleft dinners and see for yourself the impact we have on people's lives.
• Help fight the loneliness epidemic in big cities.

⌘ Recruitment Process

• Introduction Interview (30 min): A conversation with Talent Acquisition Lead to discuss your experience, career goals, and how they align with our mission at Timeleft.
• Business Interview (30min-45min): Discussion with VP Data, your future manager, about your experience and technical skills.
• Technical Interview (1h): Hands-on session with a Senior Data Engineer covering your hard skills.
• Stakeholders Interview (30 min): Final discussion with the VP Product focused on product partnership, communication, and business impact.