Principal Advanced Analytics
Listed on 2026-10-12
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IT/Tech
Data Scientist, Data Analyst, AI Business & Operations, Business Intelligence
This is a full-time onsite role based in the location(s) posted and is performed from the designated work location five days per week. No relocation is offered.
Principal, Advanced Analytics (Forecasting & Predictive Modeling) Lead Forecasting.Translate Performance. Drive Executive Decision-Making. The Local Market Forecasting & Performance Analytics team is seeking a highly analytical, technically proficient, and AI-centric leader to serve as Principal, Advanced Analytics. This team is responsible for developing and maintaining the forecasting models, analytical frameworks, and predictive insights that enable market leaders to anticipate future performance and make informed business decisions. We provide the forecasting discipline, statistical rigor, and advanced analytical capabilities necessary to support planning, performance management, and strategic decision-making across Wireless, Fiber, and AIA.
As an AI-first organization, we expect leaders to leverage machine learning, AI-enabled analytics, advanced statistical modeling, automation, and emerging technologies to improve forecast accuracy, accelerate insight generation, and enhance organizational effectiveness. Successful candidates will embrace AI as a core component of how forecasting and analytics are performed while continuously seeking opportunities to improve model performance, scalability, and business impact.
Develop and maintain forecasting models across Wireless, Fiber, and AIA products supporting daily, weekly, monthly, quarterly, and annual planning horizons. Build market-level, channel-level, and market-by-channel forecasting models for gross adds, disconnects, and net adds. Apply advanced time-series forecasting methodologies, machine learning techniques, and predictive analytics to improve forecast accuracy and responsiveness. Develop forecasting frameworks that incorporate seasonality, promotions, pricing changes, marketing activity, competitive dynamics, economic indicators, and operational factors.
Continuously evaluate and refine model performance using back-testing, error analysis, and model validation techniques.
Design and implement statistical and machine learning models using Python and related analytical tools. Utilize forecasting methodologies including Prophet, ARIMA-type approaches, gradient boosting, ensemble techniques, and other advanced modeling frameworks where appropriate. Develop scalable forecasting processes that support multiple products, channels, markets, and planning horizons. Identify leading indicators and predictive drivers that improve understanding of future performance. Evaluate emerging analytical methodologies and technologies that enhance forecasting accuracy and business insight generation.
ForecastPerformance & Diagnostics
Monitor actual results versus forecast to identify model performance issues, forecast variance drivers, and emerging trends. Conduct forecast diagnostics to understand performance changes across products, markets, channels, and customer segments. Develop drivers-based waterfall analyses illustrating how individual business factors, opportunities, risks, and strategic actions impact forecasted outcomes. Quantify the impact of promotions, pricing changes, marketing initiatives, competitive actions, and operational performance on forecast expectations.
Develop methodologies to explain forecast changes in a clear and repeatable manner.
Build automated forecasting pipelines that reduce manual effort and improve forecast consistency. Leverage AI-enabled analytics, machine learning, automation, and agentic workflows to improve forecasting processes and accelerate insight generation. Develop scalable solutions capable of supporting increasingly granular forecasting needs across markets, channels, and products. Partner with data engineering and technology teams to improve forecasting infrastructure, data availability, and model deployment processes.
Serve as an AI champion by identifying opportunities to automate recurring analytical work and improve forecasting effectiveness.
Translate complex statistical outputs into executive-ready narratives and recommendations. Present forecast results, risks, opportunities, and business implications to senior leaders and cross-functional stakeholders. Support leadership reviews with clear…
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