Principal, Advanced Analytics – Subscriber Forecasting

DIRECTV•El Segundo, CA

2d•$134,363 - $244,036•Remote

About The Position

DIRECTV is transforming its video portfolio across Signature, BYOD, DTVi, and Genre Packs within an increasingly dynamic and competitive subscription landscape. Accurate, forward-looking subscriber forecasting is critical to enterprise planning, marketing investment, product strategy, and financial decision-making. The Principal, Advanced Analytics – Subscriber Forecasting is the senior leader responsible for architecting and governing DIRECTV’s end-to-end subscriber volume forecasting framework for designated products. This role owns the science behind forecasting Gross Adds, Churn, Reconnects, and Migrations—across run-rate expectations and scenario-based overlays. This leader combines deep expertise in time-series forecasting, survival modeling, and advanced statistical methods with automation and AI enablement capabilities to modernize DIRECTV’s forecasting ecosystem.

Requirements

5 – 7 years required, 7+ years desired experience in forecasting, advanced analytics, econometrics, or quantitative modeling.
Deep expertise in time-series forecasting, survival analysis, cohort modeling, and statistical inference.
Demonstrated experience forecasting subscription-based product volumes.
Strong proficiency in Python, SQL, and advanced analytics libraries
Experience building automated modeling pipelines and scalable analytical systems.
Familiarity with AI-driven forecasting enhancements and ensemble modeling approaches.
Strong executive communication skills and ability to defend modeling assumptions.
Advanced degree in Statistics, Economics, Data Science, Applied Mathematics, or related quantitative field preferred.

Responsibilities

Enterprise Subscriber Volume Forecasting Lead forecasting methodologies for Gross Adds, Churn, Reconnects, and Migrations across DIRECTV’s video portfolio.
Develop integrated forecasting frameworks that reconcile acquisition inflow, tenure-based churn dynamics, reconnect behavior, and product migrations.
Produce baseline (run-rate) forecasts and overlay models reflecting strategic initiatives, competitive shifts, seasonality, and macro impacts.
Ensure forecasts are transparent, defensible, and aligned across Marketing, Finance, Product, and Executive Leadership.
Advanced Forecasting Methodologies Apply and evolve advanced forecasting techniques, including: Time-series modeling (ARIMA, SARIMA, state-space models) Hierarchical forecasting frameworks Survival analysis and hazard modeling for churn dynamics Cohort-based and tenure-based decay modeling Machine learning approaches (GBM, XGBoost, LSTM, ensemble methods)
Design migration models to capture movement across packages, platforms, and pricing constructs.
Incorporate industry trend signals, competitive dynamics, and structural shifts into forecasting assumptions.
Continuously test, backcast, and refine models to improve accuracy and reduce bias.
Tenure Dynamics & Behavioral Modeling Develop survival curves and hazard functions to model churn behavior across tenure cohorts.
Analyze lifecycle inflection points and structural breakpoints affecting retention and reconnect rates.
Build cohort-level forecasting models that capture evolving subscriber behavior over time.
Translate behavioral dynamics into actionable forecasting assumptions for enterprise planning.
Scenario Planning & Overlay Strategy Construct scenario frameworks that quantify impacts from: Pricing actions Promotional intensity Competitive entry or disruption Packaging shifts Product transitions
Lead sensitivity analysis and stress testing to inform executive decision-making.
Provide structured, data-driven recommendations around forecast risks and opportunities.
Automation & AI Enablement Architect automated forecasting pipelines that reduce manual intervention and increase model scalability.
Build reproducible workflows using Python, SQL, and modern data orchestration tools.
Integrate AI and machine learning into forecasting workflows to enhance pattern detection, anomaly identification, and dynamic recalibration.
Develop self-service dashboards and monitoring systems that track forecast accuracy and model drift.
Modernize legacy forecasting processes into an AI-enabled forecasting ecosystem.
Cross-Functional Leadership & Governance Serve as the enterprise authority on subscriber volume forecasting methodology.
Partner closely with Finance, Marketing, Product, Strategy, and Operations to align on assumptions and forecast outputs.
Establish governance standards for forecasting accuracy, version control, and scenario documentation.
Communicate complex modeling outputs to senior executives in a clear and structured manner.