Staff Data Analyst

Role overview

Strategic analytics

• Work with leadership to identify company-level problems that can improve top-line and bottom-line metrics.
• Drive strategic initiatives across multiple domains and product lines with measurable business impact.
• Own broad data products and business questions end to end, including data-organization-level questions.
• Influence domain roadmap and strategy through analytical work and clear recommendations.
• Recommend actions and decisions for business and product stakeholders rather than presenting options without a point of view.

Stakeholder leadership

• Navigate ambiguous questions and organizational challenges across multiple stakeholder groups.
• Manage stakeholder relationships, build coalitions, influence business strategy, and unblock execution.
• Communicate technical knowledge in a didactic and approachable way to all levels of the organization.
• Demonstrate judgment in prioritizing and executing independently and through others.

Data quality and methodology

• Own key metrics with stakeholders and data peers, set data quality standards, and define metric layers.
• Ensure analytical data is accurate, reliable, and relevant while accounting for outliers, sparsity, sample size, imbalances, and missing or corrupted data.
• Cross-check analytical data against independent internal sources where relevant.
• Document methodological approaches, assumptions, caveats, statistical significance, and confidence intervals.

Team development

• Own mentorship and professional development for junior and mid-level team members.
• Tech-lead other analysts and raise the analytical standard of the team.

Required qualifications

• Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, or a similar quantitative field, or equivalent practical experience.
• At least 5 years of analytics experience with a record of analyses that changed material business decisions.
• Expert-level SQL, including window functions and large-scale analytical databases.
• Strong Python proficiency for analysis, including pandas, NumPy, SciPy, scikit-learn, and visualization libraries.
• Advanced BI platform and semantic modeling experience focused on self-service analytics.
• Excellent problem-solving, structured thinking, stakeholder influence, mentoring, and executive communication skills.

Preferred experience

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