In this role, you’ll help drive how MNTN measures, understands, and improves customer outcomes across our connected TV advertising platform. You’ll work with advertising, campaign, account, product, and performance data to deliver insights, reporting, and analytical solutions that support better decision-making across the business. This role partners closely with analytics, engineering, product, and business stakeholders to translate complex data into actionable recommendations and scalable customer analytics capabilities. What you'll do: Analyze customer behavior, campaign performance, product usage, account health, retention, and growth opportunities to identify actionable insights. Design and maintain scalable data models and analytical datasets that support customer reporting, segmentation, forecasting, benchmarking, and executive reporting. Build dashboards, recurring reports, and self-service analytics solutions that help stakeholders monitor performance and make informed decisions. Translate ambiguous business questions into structured analyses, clear findings, and practical recommendations. Apply analytical and statistical techniques, including segmentation, cohort analysis, forecasting, anomaly detection, and performance driver analysis, to solve customer-focused business problems. Partner with cross-functional teams to define metrics, improve data quality, and ensure consistent reporting across the organization. Validate analyses and reporting outputs through rigorous QA practices to maintain trust and accuracy. Communicate insights, methodologies, and recommendations effectively to both technical and non-technical audiences. What success looks like: You deliver accurate, high-quality customer analysis that helps teams understand performance, diagnose issues, and take action. You build trusted data models and reporting foundations that support customer analytics use cases at scale. Your work is well-documented, maintainable, and easy for teammates and stakeholders to understand. You independently drive ambiguous customer or business questions from initial request to clear recommendation. You clarify the problem, identify the right data, validate your findings, and communicate the answer in a way that is useful to both technical and non-technical audiences. You balance speed and rigor. You can move quickly when needed, but you maintain strong QA practices and a high bar for accuracy. You use advanced analytics pragmatically. You know when a simple SQL analysis is enough, when a cohort or segmentation analysis is useful, and when a lightweight predictive model or forecast can help the business make better decisions. You build trust with stakeholders by consistently delivering reliable data, clear explanations, and thoughtful recommendations.