• Own Data & Analytics Infrastructure - Centralize and structure data across DTC, retail, marketplace, paid media, subscription, operations, and finance systems - Partner cross-functionally to consolidate fragmented reporting into a scalable data warehouse and/or data lake environment - Build robust data models supporting contribution margin, cohort analysis, and channel-level performance visibility - Establish and document standardized KPI definitions across departments - Reduce reliance on manual spreadsheets and ad hoc reporting • Build Decision-Driving Dashboards & KPI Frameworks - Design and maintain executive-level dashboards in BI tools, especially Looker - Own the company-wide KPI framework, including: - Blended and channel CAC - Contribution margin by channel, product, and customer - Cohort-based LTV and payback - Marketplace and retail profitability - Inventory productivity and working capital visibility - Produce clear weekly and monthly executive summaries - Monitor leading vs. lagging indicators and proactively surface risks and opportunities • Drive Cross-Functional Performance Insights - Partner with Growth to evaluate acquisition efficiency, creative performance, and media mix effectiveness - Support Finance with revenue modeling, margin expansion analysis, and investment evaluation - Partner with Retail and Marketplace teams to assess trade spend effectiveness and promotional ROI - Analyze syndicated retail data to identify share trends, velocity shifts, distribution changes, and competitive insights - Deliver actionable recommendations that inform capital allocation and strategic trade-offs • Forecasting, Modeling & Advanced Analytics - Build and enhance financial and operational models grounded in strong business economics and unit economics principles - Support scenario planning and long-range forecasting - Develop predictive analyses such as LTV modeling, churn analysis, demand forecasting, and margin simulations - Leverage AI tools to improve forecasting accuracy, automate insight generation, and detect anomalies - Continuously elevate the analytical sophistication of the organization

• Serve as the go-to analytics partner for the VP of New Business, VP of Existing Business, VP of Partnerships, CRO, and VP RevOps, providing strategic insights and operational visibility across their books of business • Build and maintain dashboards, scorecards, and ad hoc reporting to support revenue performance tracking across new, retention, expansion, and renewal motions • Provide strategic recommendations that address identified pipeline and funnel risks and escalate actionable insights to executive stakeholders • Partner across all Revenue teams to identify, implement, and evaluate strategic growth initiatives • Drive AI alignment and development of automated insights across pipeline operations and campaign effectiveness analysis • Communicate findings, insights, and recommendations clearly and effectively across weekly, monthly, and quarterly business reviews with cross-functional stakeholders and senior leadership • Own and update headcount capacity models, territory plans, and quota allocations for the full Revenue team in alignment with GTM strategy • Partner with RevOps and Finance on compensation execution, ensuring accurate payout calculations and alignment between performance data and plan mechanic. • Deliver period-end insights and retrospectives, including performance by segment, product, and rep—along with qualitative takeaways and forward-looking recommendations • Drive proactive analytics to identify risks and opportunities before they surface, informing leadership decisions and action planning. • Manage inbound ad hoc reporting requests while maintaining focus on high-impact, scalable reporting initiatives • Support quarterly and annual planning efforts with data-backed insights that inform target-setting, revenue modeling, and resource allocation • Partner with RevOps systems team and cross-functional stakeholders to define and evolve business requirements and enable high-quality data infrastructure • Partner with Revenue team members and Data Analytics partners to support ad-hoc requests and deep dives. Enable a self-service analytics culture by driving adoption of our BI tools and dashboards to make insights consistent and accessible

• As a member of the data team, in the role of Senior Data Analyst, you will be responsible for the maintenance of existing and development of new critical financial and operational business intelligence dashboards • You will leverage the data team’s stack (Fivetran, Snowflake, dbt, Metaplane, Airflow, and Github) to work with source data that impacts business intelligence • Interface with teams and stakeholders across the organization to identify reporting needs, turning those conversations into action items and reporting deliverables • Be a resource and leader when it comes to our data so you can empower our colleagues to understand their business and make better decisions • Partner with the data team and others to monitor and ensure data accuracy, and collaborate on solutions for areas of improvement • Success in this role involves delivering actionable insights that influence decisions, reliable reporting that’s trusted by our colleagues, and timely delivery of analysis to support fast moving initiatives • You must be a BI rockstar • You will be building and improving on our reporting and analytics offering in Sigma Computing, and eventually taking on ownership of it • Develop strong, collaborative relationships across the organization and a deep understanding of our data and what we’re equipped to report on • Become a trusted and dependable resource to our colleagues when it comes to data and insights • Contribute to our dbt modeling by leveraging SQL and git

• Analyze large and complex data sets to identify trends, patterns, and insights that drive product strategy, experimentation, and AI-enabled decision-making. • Design and build scalable dashboards, data models, and self-serve tools that empower Product and cross-functional teams to independently answer key business questions. • Partner closely with Product Managers to support A/B testing, conversion optimization, SEO performance, and matching tool enhancements . • Develop and validate analytical and classification models, ensuring reliable and deterministic behavior where required for production decision systems. • Translate ambiguous business questions into structured analytical frameworks and AI-assisted workflows. • Present findings and strategic recommendations to senior leadership in a clear, actionable, and decision-oriented manner. • Monitor performance of experiments, product initiatives, and AI-driven systems, recommending iterative improvements based on data. • Stay current with emerging analytics and AI technologies, proactively identifying opportunities to responsibly scale AI capabilities across the organization.