
Salla
Senior Product Data Analyst
- Permanent
- Jeddah, Saudi Arabia
- Experience 2 - 5 yrs
Job expiry date: 08/10/2026
Job overview
Date posted
24/08/2026
Location
Jeddah, Saudi Arabia
Salary
SAR 20,000 - 30,000 per month
Compensation
Comprehensive package
Experience
2 - 5 yrs
Seniority
Senior & Lead
Qualification
Bachelors degree
Expiration date
08/10/2026
Job description
In this role you will help shape how Salla builds and improves products through data, partnering with Product Managers, Engineers, Designers, and the Data team to turn customer behaviour and product performance into clear decisions. You will own analytics for a product area end to end, from defining success metrics and measurement plans to analysing experiments, monitoring launches, and recommending next steps. You will partner with product teams to translate questions and hypotheses into clear KPIs and success criteria, and you are responsible for owning analytics across key product journeys, including funnels, feature adoption, engagement, conversion, retention, and segmentation. Your responsibilities include conducting deep-dive analyses to diagnose performance changes, uncover root causes, and recommend product opportunities. You will design and analyse A/B tests and impact evaluations, including metric selection, guardrails, validation checks, and decision recommendations, and you are responsible for developing and validating tracking plans for new features. You will measure product launches and build dashboards and self-serve tools for monitoring product health, and you are responsible for communicating findings, business impact, and trade-offs clearly while contributing to team best practices and supporting junior analysts. Given Salla's complex, large-scale products, you will often face questions without an existing playbook, requiring you to learn domains quickly, synthesise across messy inputs, and decide the right level of analysis for each decision.
Required skills
Key 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
Experience & skills
- Bring 4 or more years of experience in product analytics, data analytics, or a related role within a technology or digital-product environment
- Demonstrate advanced SQL skills and experience working with large, complex datasets
- Show strong understanding of product metrics including funnels, cohorts, conversion, retention, and feature adoption
- Have hands-on experience with product experiments and a solid understanding of hypothesis testing, confidence intervals, statistical power, and common A/B testing pitfalls
- Show experience with event-based product data, tracking plans, implementation validation, and data-quality checks
- Demonstrate proficiency with a BI tool such as Looker, Metabase, or Tableau, plus working knowledge of Python or R
- Show strong product judgement and the ability to manage analytical work independently in ambiguous situations
- Demonstrate excellent communication and stakeholder-management skills, with the ability to influence product decisions through data
- Proficiency in Arabic and experience working in Saudi Arabia or the wider GCC is nice to have
- Experience in e-commerce, marketplaces, fintech, or SaaS products is nice to have
- Familiarity with tools such as Amplitude, Mixpanel, dbt, ClickHouse, or BigQuery is nice to have
- Knowledge of causal inference, quasi-experimental approaches, or Bayesian methods is nice to have