Product Data Analyst – Riyadh

About the role

We are seeking a Product Data Analyst to join our digital product team in Riyadh. You will turn product data into actionable insights that drive product development and business decisions, focusing on user behavior, data quality, and product metrics.

Key responsibilities

• Define, manage, and document key product metrics such as activation, job application journeys, recruiter engagement, and AI service performance.
• Lead the creation and governance of a standardized Job Title Taxonomy to improve data consistency.
• Identify, analyze, and resolve data quality issues across production data.
• Design and maintain data tracking plans, specifying events and properties for engineering implementation.
• Conduct end‑to‑end analysis, from business question formulation and SQL query writing to delivering actionable recommendations.
• Design and evaluate experiments, including sample size calculation and statistical significance testing.
• Build and maintain dashboards and underlying data models for self‑service analytics.
• Validate data accuracy, investigate anomalies, and challenge data that does not reflect actual product behavior.
• Present insights and recommendations to Product, Engineering, and Executive teams.

Required profile

• 2–5 years of experience in data analytics, with at least 2 years supporting a live digital product.
• Bachelor’s degree in Statistics, Mathematics, Data Science, Computer Science, or a related quantitative field, or equivalent practical experience.
• Excellent English communication skills; Arabic is strongly preferred.
• Must be based in Riyadh, Saudi Arabia.

Required skills

• Advanced SQL (complex joins, aggregations, query optimization).
• Proficiency in Python or R for advanced data analysis.
• Experience with a BI platform such as Power BI, Tableau, Looker, or Metabase, including data modeling.
• Hands‑on product analytics and data tracking plan design.
• Experimentation, statistical analysis, sample sizing, and significance testing.
• Data cleaning and resolution of production data quality issues.
• Familiarity with dbt or data‑warehouse modeling (preferred).