Data Science and Analytics Manager

Summary:

The Manager, Advanced Analytics will report to the Director, Advanced Analytics and will lead developing advanced analytics, building Machine Learning models, and delivering strategic insights that drive enterprise wide decision-making. This role will partner in developing analytical roadmaps, partner with senior leaders across Customer Experience & Operations, IT, Marketing, Pricing, Finance, and the Existing Customer business, and provide data backed recommendations that influence revenue growth, customer retention, pricing strategies, and operational performance. The Manager will own the design and execution of scalable analytical frameworks—including Customer Lifetime Value, segmentation, test and learn programs, and subscriber trend modeling—to enable fast, data driven prioritization across the organization. Success in this role will be defined by elevating analytic maturity, shaping cross functional strategy, and enabling business units to make informed decisions that materially impact profitability, customer experience, and long-term value creation.

Duties and Responsibilities:

• Lead development of Advanced Data science (DS) and Machine Learning (ML) models across Customer care, pricing and other enterprise groups. 

• Explore and develop new high value use cases to drive enterprise growth using DS and ML techniques.

• Lead the development and optimization of enterprise pricing, forecasting, and customer value models, partnering with Pricing and Finance to shape strategic pricing decisions and long-term revenue plans.

• Oversee cross functional execution of price, offer, and customer communication changes, ensuring alignment between Pricing, IT, Marketing, and Customer Experience.

• Own the analytical strategy and roadmap that drives Customer Lifetime Value growth, using advanced analytics to identify opportunities across upgrades, collections, proactive outreach, and support channels.

• Guide and govern existing customer segments and campaign pricing, including offer strategy, commercial guardrails, execution governance, and performance measurement.

• Direct a robust test and learn agenda, including experiment design, funnel optimization, and performance evaluation to accelerate customer growth and operational efficiencies.

• Oversee enterprise analysis of subscriber trends, lifecycle patterns, and customer journey performance, partnering with Customer Experience leaders to design best in class, Churn treatments

• Drive segmentation strategy and implementation, ensuring segments, propensity models, and personalization frameworks are fully leveraged across customer retention, pricing, loyalty, communications.