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About this Staff Data Analyst role at Salla

Salla · Onsite · Jeddah, Makkah Province, Saudi Arabia

We are looking for a Staff Data Analyst within Salla’s data organization.

This is a senior individual contributor role. Rather than executing a defined backlog, you will work with leadership to identify which company-level problems are worth solving, specify them from vague requirements, and lead the analytical work that moves top-line and bottom-line metrics. Your scope spans multiple domains and product lines, you will tech-lead other analysts, and your impact is measured by the decisions you change and the capability you build in others.

Responsibilities

  • Work with leadership to proactively identify key company-level problems to solve, driving direct impact to top-line and bottom-line metrics.
  • Drive strategic initiatives that span multiple domains and product lines, with measurable business impact.
  • Take independent end-to-end ownership of broad data products and business questions, as well as questions at the data organization level.
  • Demonstrate excellent judgement in prioritizing and executing both independently and through others.
  • Navigate ambiguous questions and organizational challenges to land impact, managing upward, downward, and sideways across multiple stakeholders.
  • Recommend clear actions and decisions for your business and product stakeholders to take, rather than presenting options without a point of view.
  • Influence the roadmap and strategy of your domain, persuading stakeholders to act on the back of your analytical work.
  • Fully manage stakeholder relationships: identify new stakeholders, build coalitions to influence business strategy, and leverage them to unblock execution.
  • Communicate all aspects of your technical knowledge in a didactic and approachable way to all levels of the organization.
  • Own the development and maintenance of key metrics with your stakeholders and data peers, setting data quality standards and defining metric layers.
  • Ensure the data behind every analysis is accurate, reliable, and relevant, accounting for outliers, sparsity, sample size, imbalances, and missing or corrupted data, and cross-checking against independent internal sources where relevant.
  • Clearly call out the methodological approaches considered, and document assumptions and caveats, statistical significance, and confidence intervals to prevent misinterpretation by stakeholders.
  • Own the mentorship and professional development of junior and mid-level team members.

Requirements

  • Bachelor’s degree in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, or similar), or equivalent practical experience.
  • 5+ years in analytics, with a demonstrable track record of analyses that changed material business decisions.
  • Expert-level SQL, including window functions and working with large-scale analytical databases.
  • Strong proficiency in Python for analysis (pandas, NumPy, SciPy, scikit-learn, visualization libraries).
  • Advanced experience with BI platforms and semantic modelling, with a focus on enabling self-serve analytics rather than producing dashboards on request.
  • Excellent problem-solving skills and structured thinking applied to ambiguous or technically complex problems.
  • Demonstrated ability to influence senior stakeholders without direct authority, build coalitions, and hold a position under pressure when the evidence supports it.
  • Evidence of tech-leading or mentoring other analysts and raising the standard of a team, not only strong individual output.
  • Excellent written and verbal communication, with the ability to make complex analysis legible to an executive audience.

Nice to have

  • Experience in e-commerce, marketplaces, fintech, or another high-volume transactional domain.
  • Familiarity with modern warehousing and transformation tooling (dbt, columnar databases such as ClickHouse or BigQuery).
  • Experience with event-level product analytics and instrumentation design.
  • Experience supporting pricing, monetization, or revenue modelling work.
  • Working knowledge of version control and code review practices applied to analytics work.
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