Product Analyst

Roles and Responsibilities:

• Analyse and interpret SaaS product and growth metrics—including activation, conversion, retention, churn, expansion, ARPU, LTV, and funnels—to inform product, growth, and revenue decisions.
• Partner with Product Managers to define success metrics and evaluate feature launches and roadmap initiatives.
• Proactively identify trends, anomalies, and opportunities in product and business data, and surface actionable insights to stakeholders.
• Support experimentation and continuous improvement initiatives (A/B tests, feature rollouts, UX changes) through analysis and clear recommendations.
• Own analysis and insights using product analytics tools such as Mixpanel or Amplitude.
• Build, own, and maintain dashboards and reports in BI tools (e.g., Power BI, Looker Studio) for Product, Growth, and Finance teams.
• Use GA4 and tools like Microsoft Clarity to complement product analytics with acquisition and qualitative behavioural insights.
• Ensure product tracking is consistent by collaborating with Product and Engineering on event definitions, taxonomy, and validation.
• Collaborate closely with the Data Engineering team on the definition, retrieval, and presentation of data, ensuring it is relevant, accurate, and aligned with business needs.

Required Skills & Experience

• 3–6 years of experience as a Product Analyst, Data Analyst, or similar role in a B2B SaaS or product-led company.
• Strong understanding of SaaS and growth metrics (funnels, cohorts, retention, churn, LTV, subscription billing and revenue metrics).
• Hands-on experience with Mixpanel or Amplitude.
• Familiarity with GA4 and qualitative/UX analytics tools such as Microsoft Clarity.
• Strong SQL skills for analysis (joins, aggregations, CTEs).
• Experience with BI or reporting tools (e.g., Looker, Power BI, Metabase, Tableau).
• Excellent communication skills and ability to influence decisions with data.

Nice to Have

• Experience supporting A/B testing and experimentation frameworks.
• Experience with Python for automation, transformation, or API integrations.
• Knowledge of data validation frameworks and monitoring tools.
• Experience working with privacy, consent, or compliance-focused products.