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Data Analytics Manager, Pay TV
hace 17 horas
The Data Analytics Manager – Pay TV will lead the analytics strategy supporting key business decisions related to subscribers, churn, revenue, programming, sales, and distribution. This role combines team leadership, advanced analytics, and deep understanding of the Pay TV business to maximize profitability, retention, and operational efficiency. Reports to: Head of Data / Director of Analytics / VP Strategy RESPONSIBILITIES Lead and develop a team of Data Analysts. Define analytics priorities aligned with business objectives. Establish data quality, governance, and best practices. Translate business needs into clear analytical requirements. Pay TV Business Analytics Analyze key KPIs: subscribers, churn, ARPU, revenue, packages, and promotions. Evaluate performance by operator, region, and customer segment. Measure impact of pricing, bundles, and channel lineup changes. Analyze viewing patterns and ratings by channel, time slot, and content. Retention, Churn & Revenue Optimization Build churn and customer segmentation models. Identify cancellation drivers and retention opportunities. Measure effectiveness of promotions and loyalty programs. Optimize LTV in collaboration with marketing and sales teams. Executive Reporting & Decision Support Build executive dashboards and operational reports. Present clear, actionable insights to senior leadership. Translate complex data into business-oriented narratives. Data Governance & Architecture Ensure data consistency across billing, CRM, ratings, and distribution systems. Partner with technology teams to improve data pipelines and quality. Define official metrics and single source of truth. Planning & Forecasting Support subscriber, revenue, and churn forecasting. Participate in annual planning and KPI tracking. REQUIREMENTS 6–8+ years of experience in data analytics, preferably in Pay TV, telecom, or media. Proven experience leading analytics teams. Advanced SQL proficiency. Experience with BI tools (Tableau, Power BI, Looker). Knowledge of billing systems, CRM, and subscription metrics. Strong background in churn, ARPU, cohort, and segmentation analysis. Strong leadership and influencing skills. Strategic business mindset. Ability to communicate insights to non-technical audiences. Strong organizational and stakeholder management skills. Results-driven attitude. Key KPIs Churn reduction. ARPU and LTV growth. Dashboard quality and adoption. Reporting and forecasting accuracy. Business impact of analytics insights. Analytics team performance and development. #J-18808-Ljbffr
