• Own end-to-end funnel analysis across all product areas, identifying drop-off points and conversion opportunities • Analyze user journeys through activation, engagement, and retention to uncover friction points for different cohorts and user segments • Partner with Product teams to prioritize and measure funnel improvement initiatives • Define and track customer value metrics (activation, adoption, retention, engagement, conversion), business KPIs (ARR, churn, LTV, CAC) and translate them into actionable product signals • Create insightful dashboards showing how product improvements impact customer value and business outcomes • Autonomously design and lead A/B tests focused on funnel conversion improvements, partnering with stakeholders • Proactively propose experiments to unlock new customer value levers and optimize conversion rates • Select success metrics, analyze results, and interpret statistical significance to inform decisions • Develop and maintain data models using dbt (incremental models, snapshots, documentation, generic tests, macros) • Apply data modeling techniques (star/snowflake schema, data-marts, SCDs) and optimize BigQuery queries using clustering/partitioning for performance and cost efficiency • Work as embedded peer within Product squads, participating in syncs and discovery sessions to surface customer pain points and bottlenecks • Communicate findings effectively to technical and non-technical stakeholders and mentor junior analysts to promote excellence

• Analyze performance of direct mail, email, and digital fundraising campaigns, including acquisition, renewal, reactivation, and upgrade efforts. • Evaluate donor behavior across channels, identifying patterns in response, giving frequency, average gift, and lifetime value. • Support list strategy, segmentation, circulation planning, and channel integration through data-driven insights. • Assess digital-to-mail and mail-to-digital interactions to inform coordinated fundraising strategies. • Use SQL to query, extract, and manipulate large donor and campaign datasets from client databases and internal systems. • Leverage AI-assisted analytical techniques (e.g., automated pattern detection, forecasting support, anomaly detection, and natural language summarization) to enhance analytical efficiency and insight quality. • Perform segmentation, cohort analysis, and trend analysis to support targeting, personalization, and testing strategies. • Translate complex analytical findings into clear, actionable recommendations for strategists, account teams, and clients. • Design, build, and maintain Power BI dashboards and reports that track key fundraising KPIs, including response rate, cost per dollar raised, ROI, and donor lifetime value. • Ensure dashboards are intuitive, accurate, and tailored to both internal stakeholders and nonprofit clients. • Standardize reporting frameworks and definitions across campaigns and clients where appropriate. • Incorporate AI-enabled features and workflows within Power BI and related Microsoft tools to improve automated insights, narrative reporting, and performance monitoring. • Partner with internal teams and clients to ensure donor data cleanliness, consistency, and proper structure. • Identify data quality issues and proactively recommend solutions to improve reporting accuracy and analytical reliability. • Document data sources, assumptions, and methodologies to support transparency and repeatability. • Collaborate with strategy, account management, creative, and production teams to inform campaign planning and optimization. • Participate in client meetings as a data subject-matter expert, presenting insights and explaining analytical approaches. • Support test design, evaluation, and post-campaign analysis for direct mail and digital initiatives. • Mentor junior analysts and contribute to the development of agency-wide analytics best practices. • Identify opportunities to improve analytical workflows through better use of Microsoft tools and automation. • Identify and recommend responsible uses of AI to streamline reporting, automate repetitive analytical tasks, and improve scalability while maintaining data accuracy and governance standards. • Evaluate and recommend enhancements to data models, dashboards, and reporting processes.

• Lead a team of data analysts in the migration, cleansing, and integration of data from multiple legacy systems • Develop and implement data quality standards and processes • Analyze complex datasets to identify trends, patterns, and insights to support decision-making • Collaborate with cross-functional teams to ensure data integrity throughout the ERP implementation • Create comprehensive reports and dashboards for stakeholders • Lead and mentor team members and provide technical guidance

• Translate business requirements to analytical outputs in the form of dashboards • summarize ML outputs to actionable insights • Supports data exploration and profiling, and works closely with DE team to build data models • Mentors/trains junior analysts to grow their expertise • Work with cross-functional teams to deliver the outcomes • Coordinates with DE/SE to perform data validation and compares against client control totals • Coordinates with DS team (as required) to conduct analytical QA on DS outputs • Captures client requirements from BRDs and works closely with product managers to get them fleshed out • Reviews analytical outputs and prepares insights to present to customers • Leverages domain and data understanding to drive insights and build intelligence dashboards