Role Description We’re looking for a finance focused Senior Data Analyst to join our Business Analytics Engineering team. In this role, you’ll be working with cutting-edge online advertising technology and delivering top-notch data transformations, analytics, and visualizations. Our advertising spans billions of requests across thousands of dimension attributes handled by dozens of applications. Understanding the flow of data and integration points will be crucial to building representations ranging from high-level summary insights to low-level minutiae. - Become an expert on MNTN finance, accounting & rev-ops data pipelines to pull thoughtful insights around the wholistic state of MNTN performance. - Forecasting: Apply a deep understanding of revenue modeling using efficient code, resulting in clear and accurate forecasts to be used for analytical and operational reporting. - Reporting & Analytics: Conduct regular data analysis and present insightful reports to internal stakeholders. Deliver high-quality, repeatable dashboards and analytics solutions. - Cross-Functional Collaboration: Work closely with teams throughout the company (including C-suite) to translate data findings into actionable insights and recommendations. Qualifications - 5+ years experience in financial analytics or similar. - 2+ years experience in Tableau or a similar dashboarding tool. - Experience with complex financial & revenue data. - Extensive SQL experience with the ability to write scalable, maintainable queries. - Advanced Excel/spreadsheet and analytical skills. - Demonstrated ability to create data visualizations for use in communication with others through reports and dashboards. - A self-starter attitude and ability to work in a fast-paced but fun environment. - Ability to multi-task, be extremely detail-oriented, and thrive in an entrepreneurial environment characterized by growth and change. - Ability to manage multiple stakeholders and multiple priorities. Requirements - Bonus: Project management and organizational skills. - Bonus: 2+ years experience in martech or adtech with a demonstrable understanding of ad buying, attribution, and analytics. Benefits - 100% remote within the US. - Flexible vacation policy. - Annual vacation allowance for travel related expenses. - Three-day weekend every month of the year. - Competitive compensation. - 100% healthcare coverage. - 401k plan. - Flexible Spending Account (FSA) for dependent, medical, and dental care. - Access to coaching, therapy, and professional development.

• Leading the validation of predictive and machine-learning models for specific business needs using statistics and advanced mathematical techniques • Guiding a team and/or project through providing solutions to business problems leveraging statistics and quantitative tools/techniques • Assessing and validating models, methodologies, and analytical frameworks • Communicating technical theories and models to a non-technical audience • Evaluating the appropriateness of analytical methods used and assessing their justification

• Author, maintain, and version taxonomies, business term definitions, and classification hierarchies in the governance platform. • Translate approved governance decisions into structured, testable data rules and apply rule IDs consistently across taxonomies. • Run routine rule-library analysis to detect duplicates, conflicts, and coverage gaps, and prepare findings for governance review. • Maintain metadata, documentation, and change history so definitions and rules remain traceable and auditable. • Support intake and triage of new rule and definition requests from Data Operations and business stakeholders. • Prepare reference data and golden-record candidates for governance certification, flagging anomalies and exceptions. • Produce clear documentation and quick-reference guides that help stewards and analysts apply standards independently. • Assist in preparing governance reporting, dashboards, and stakeholder updates.

• Build and own the reporting layer for Support • Partner with Support leadership for data-driven decisions • Maintain the multi-signal model behind bug and issue prioritization • Design dashboards for internal and customer-facing audiences • Own data quality, governance, and reliability for Support data products • Surface Voice of Customer trends to Product, Engineering, and GTM