Senior Analytics Solutions Analyst

Role overview This senior analytics role connects paid media investment to downstream business outcomes, translating platform-level metrics into full-funnel performance and long-term value signals. The position sits at the intersection of marketing, channel strategy, and executive decision-making, with secondary responsibility for web analytics infrastructure that supports measurement accuracy.

Responsibilities - Analyze and connect paid media platform performance (spend, CPL, CPC, CPA) to full-funnel outcomes from lead and application through enrollment, student LTV, and ROAS - Partner with paid media and channel teams to build attribution and measurement frameworks linking ad platform data to enrollment and revenue outcomes - Develop and maintain ROAS and LTV analyses that connect media spend to long-term student value and program-level profitability, incorporating retention and graduation signal where available - Design, build, and optimize scalable data models, pipelines, and transformation workflows in Databricks - Design and enhance Power BI dashboards and reporting experiences, including semantic modeling and advanced DAX - Support web analytics tagging validation and event data quality to ensure clean inputs for paid media measurement - Contribute to Marketing Mix Modeling initiatives, including channel spend optimization, geo-experiments and lift tests, and budget allocation recommendations - Conduct funnel, cohort, channel, conversion, and forecast analyses, and present findings to Director, VP, and Executive stakeholders

Requirements - Proven experience connecting paid media platform performance to full-funnel business outcomes including enrollment, LTV, and ROAS - Strong background in paid media measurement, including multi-touch attribution and campaign performance analysis across platforms such as Google Ads, Meta, and LinkedIn - Experience with Marketing Mix Modeling, media mix simulation, or geo-experiments and lift tests to validate channel effectiveness - Advanced SQL proficiency, including CTEs, window functions, query optimization, and large-scale data transformation - Strong hands-on experience with Power BI, including semantic modeling, advanced DAX, and dashboard storytelling - Strong experience with Databricks, including Delta Lake, PySpark, notebooks, and workflows - Working knowledge of web analytics platforms (e.g., Adobe Analytics, GA4) sufficient to support tagging validation and data quality - Strong executive communication and data storytelling skills, with the ability to navigate ambiguity and lead through undefined problem spaces

Nice to have - Experience with LTV modeling or long-term value analysis, such as cohort-based retention or graduation value - Experience with Python, statistical modeling, or advanced analytics workflows - Exposure to AI-enabled analytics, automated insight generation, or intelligent reporting frameworks - Background in product analytics, experimentation, or growth analytics - Experience in analytics engineering or modern data architecture - Familiarity with data clean rooms or audience data-sharing measurement (e.g., LiveRamp, Trade Desk, retail or media networks) - Experience working in high-growth, fast-paced environments