Staff Data Analyst

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.