Staff Data Analyst
Mid-Senior levelBachelor's DegreeData AnalystInformation Technology and ServicesAI and Data Analytics
About the role
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, im…