Senior Product Data Analyst

About the Role

Responsibilities

• Partner with product teams to translate questions and hypotheses into clear KPIs and success criteria.
• Own analytics across key product journeys, including funnels, feature adoption, engagement, conversion, retention, and segmentation.
• Conduct deep-dive analyses to diagnose performance changes, uncover root causes, and recommend product opportunities.
• Design and analyse A/B tests and impact evaluations, including metric selection, guardrails, validation checks, and decision recommendations.
• Develop and validate tracking plans for new features.
• Measure product launches and build dashboards and self-serve tools for monitoring product health.
• Communicate findings, business impact, and trade-offs clearly while contributing to team best practices and supporting junior analysts.

Requirements

• 4+ years of experience in product analytics, data analytics, or a related role within a technology or digital-product environment.
• Advanced SQL skills and experience working with large, complex datasets.
• Strong understanding of product metrics, including funnels, cohorts, conversion, retention, and feature adoption.
• Hands-on experience with product experiments and a solid understanding of hypothesis testing, confidence intervals, statistical power, and common A/B-testing pitfalls.
• Experience with event-based product data, tracking plans, implementation validation, and data-quality checks.
• Proficiency with a BI tool such as Looker, Metabase, or Tableau, plus working knowledge of Python or R.
• Strong product judgment and the ability to manage analytical work independently in ambiguous situations.
• Excellent communication and stakeholder-management skills, with the ability to influence product decisions through data.

Nice to Have

• Proficiency in Arabic and experience working in Saudi Arabia or the wider GCC.
• Experience in e-commerce, marketplaces, fintech, or SaaS products.
• Familiarity with tools such as Amplitude, Mixpanel, dbt, ClickHouse, or BigQuery.
• Knowledge of causal inference, quasi-experimental approaches, or Bayesian methods.