Head of Personalization Intelligence

Bank of America•Newark, NY

About The Position

The Head of Personalization Intelligence leads the data, analytical, and insight capabilities that power personalized client experiences. Reporting directly to the Managing Director, Analytics & Information Executive, this leader builds and advances an integrated intelligence layer that connects client signals, personas and insights, lifetime value, analytics, and measurement. The goal is to create a dynamic understanding of clients and their needs, making insights increasingly timely and actionable across channels. The role sets strategy and establishes reusable data, analytical, and measurement frameworks. It leads the development of client understanding, behavioral signals, value methodologies, and measurement approaches, and partners with Product, Marketing, Technology, and Enablement to operationalize intelligence across the organization. The position advances capabilities from historical and batch-oriented analytics toward predictive, dynamic, and real-time intelligence, while setting appropriate standards and governance. The Head builds a high-performing team spanning analytics, data science, decision science, client insights, and measurement. The role is accountable for the underlying data, signals, analytical methodologies, client insights, personas, lifetime-value frameworks, and measurement capabilities that enable personalization, while working with partner organizations to translate them into client and business outcomes.

Requirements

Senior leadership experience across personalization, client analytics, decision science, data science, marketing analytics, or related disciplines.
Demonstrated experience building scalable analytics and personalization capabilities.
Deep expertise in areas such as segmentation, behavioral signals, predictive modeling, lifetime value, experimentation, incrementality, and measurement.
Experience applying advanced analytics, machine learning, and AI to client intelligence and personalization.
Experience partnering with Technology teams to operationalize analytical capabilities and move toward real-time use cases.
A strong track record working across Product, Marketing, Data, Analytics, and Technology organizations.
Ability to translate complex analytical capabilities into clear business strategies and influence senior stakeholders.

Responsibilities

Define and lead the strategy for data and intelligence capabilities that enable personalization.
Create an integrated, reusable ecosystem across client signals, client understanding, value, analytics, and measurement.
Establish common data, analytical, and measurement frameworks for reuse across products and channels.
Lead development of personas, segments, client insights, and analytical frameworks that deepen understanding of client needs, behaviors, preferences, and opportunities.
Integrate behavioral, transactional, engagement, and other available data to create a holistic view of clients.
Translate complex data into actionable insights for Product, Marketing, and other partners.
Lead the development of signals that identify changes in client behavior, needs, intent, engagement, and opportunity.
Establish scalable, reusable signal frameworks and determine which signals should evolve toward real-time availability based on client and business value.
Establish standards and governance for personalization data and signals.
Lead the development and evolution of lifetime-value methodologies and analytical approaches that balance near-term opportunities with longer-term client value.
Partner with Technology and Enablement to translate personalization intelligence into scalable data and analytical capabilities for use across channels.
Define data, signal, model, and analytical requirements for more dynamic and real-time intelligence, and partner with Technology on the supporting architecture.
Ensure personalization intelligence is structured for consistent consumption by downstream platforms and channels.
Establish organization-wide measurement frameworks and methodologies for incrementality, client outcomes, business outcomes, and longer-term value.
Advance experimentation and test-and-learn approaches that distinguish correlation from incremental impact.
Create feedback loops that incorporate channel interactions and outcomes into signals, personas, models, lifetime value, and future insights.
Use measurement to continuously improve personalization intelligence.
Build a unified personalization intelligence capability across analytical disciplines and develop reusable capabilities rather than one-off solutions.
Partner across Product, Marketing, Technology, Enablement, Data, and Analytics organizations, influencing senior stakeholders across organizational boundaries.
Lead and develop a high-performing team spanning analytics, data science, decision science, client insights, and measurement.