Data Manager Senior - Data Products - AI and Analytics

PNC•Dallas, PA

2d•Onsite

About The Position

At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success. As a Data Manager Senior within PNC's Data Products organization, you will be based in Pittsburgh, PA. We are seeking a highly accomplished Data Product Manager to lead the strategy, development, and delivery of enterprise-scale data, analytics, AI, and GenAI products that support retail banking portfolios, customer experiences, and operational decision-making. This role is responsible for defining product vision, establishing roadmaps, and driving the delivery of AI-ready data products, advanced analytics solutions, semantic data assets, and GenAI-enabled business capabilities. The ideal candidate will combine strong product management expertise, deep understanding of data and analytics ecosystems, and experience delivering AI-powered business solutions. This individual will partner across business, technology, data science, architecture, and governance teams to deliver reusable, scalable, and highly interoperable data products that enable self-service analytics, intelligent automation, and agentic digital experiences across retail banking value streams.

Requirements

Successful candidates must demonstrate appropriate knowledge, skills, and abilities for a role. Listed below are skills, competencies, work experience, education, and required certifications/licensures needed to be successful in this position.
Bachelors
No Required Certification(s)
No Required License(s)
No Required or Preferred Language Assessments

Nice To Haves

Analytical Thinking
Competitive Advantages
Data Analytics
Data Mining
Data Science
Machine Learning (ML)
Business Intelligence
Data Administration
Data Architecture
Data Governance
Data Warehousing
Information Management
IT Standards, Procedures & Policies
Modeling: Data, Process, Events, Objects
Root Cause Analysis (RCA)
Higher level education such as a Masters degree, PhD, or certifications is desirable.
Industry experience is typically 8+ years.
At least 5 years of prior management experience is typically required.
In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.

Responsibilities

Define and execute the multi-year roadmap for enterprise data, analytics, and AI products aligned to retail banking portfolios, customer journeys, and process families.
Design reusable, governed, and AI-ready data products that accelerate analytics, machine learning, GenAI adoption, and digital transformation initiatives.
Design reusable and AI-ready data products aligned to the organizational structure of retail banking portfolios and associated process families.
Develop highly interoperable data engineering and analytics artifacts spanning retail banking portfolios across structured, semi-structured, unstructured, and external data domains.
Lead the delivery of diagnostic, predictive, and prescriptive analytics solutions supporting customer growth, operational efficiency, risk optimization, and revenue generation.
Define enterprise standards for analytics products, model governance, explain ability, and business adoption.
Define and deliver enterprise semantic layers that enable consistent KPI definitions, business metrics, and trusted analytical experiences.
Lead strategy for enterprise business vocabularies, metadata management, taxonomies, ontologies, and knowledge graphs.
Manage data product delivery across multiple agile teams within a matrixed organization.
Drive end-to-end product execution from ideation, requirements, business case development, prioritization, implementation, launch, and adoption.
Manages all aspects of organizational data; establishes and maintains policies and procedures for planning, designing and maintaining an information bank to ensure that data services are delivered in a high-quality and profitable manner.
Provides senior leadership, direction and methodology for analysis, structure and storage of critical organizational data.
Oversees the integrity and maintenance of organizational data.
Monitors and reviews major organizational activities and goals to ensure important data needs are anticipated, and met.
Reviews and recommends policies and procedures for collecting and managing organization data.