
Staff Data Analyst
Salla · Jeddah, Makkah Province, Saudi Arabia · Hybrid
Weak hiring record · median 77 days open
All reasons
- Open 84 days
- 59% of this employer's openings are over 60 days old
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.
- 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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