Data & AI – Branch Strategy and Execution- Vice President

JPMorganChase•Columbus, OH

About The Position

Help transform our branch network through data, analytics, and AI-powered solutions that enhance how our sales teams serve clients. This role is ideal for someone who excels at turning insights into action and thrives in a fast-paced, innovative environment. You’ll need strong data and analytical judgment, clear communication, and the ability to drive alignment across groups with different priorities. As a Vice President on the Branch Strategy & Execution team, you will drive both the strategy and execution of high-impact Data & AI initiatives that improve sales effectiveness, coaching, client engagement, and operational performance. You’ll sit at the intersection of business strategy, analytics, data, technology, and AI. You will partner closely with Data Owners, Data Scientists, Product, Engineering, and Business Leaders to identify opportunities, define solutions, and lead delivery from concept through adoption. You’ll need to be passionate about turning data into actionable insights, managing data as a product, and accelerating AI capabilities through strong execution, governance, and stakeholder alignment. Success requires the ability to connect strategic objectives with practical implementation while influencing across a complex organization.

Requirements

Bachelor's degree and 5+ years of experience in analytics, strategy, product, technology, technical program management, or related disciplines
Technical program manager experience in leading complex programs, analytic initiatives, data products, or AI/ML solutions across matrixed organizations
Strong communication and storytelling skills, including the ability to tailor messages for executive and technical audiences.
Ability to collaborate effectively across functions, and demonstrated success influencing stakeholders and managing initiatives across organizations without direct authority
Strong understanding of data management, risk, controls, governance, analytics, business intelligence, data warehousing, and AI/ML concepts.
Experience designing and implementing AI solutions that prioritize user experiences, drive measurable business outcomes, and effectively integrate with human-centric workflows and decision-making processes.
Translate business problems into scalable data, analytics, and technology solutions.
Proven ability to manage multiple concurrent initiatives, prioritize effectively, and adapt to changing needs.
Champion data quality, documentation, and analytical rigor across deliverables and decision processes.
Advanced proficiency with PowerPoint, Excel, and AI-enabled productivity tools

Nice To Haves

Experience working with sales, product, data and analytic organizations
Working knowledge of how Machine Learning and AI techniques can enhance forecasting, optimization, or decisioning workflows.
Familiarity with analytic and data architecture concepts to support scalable analytics.
Understanding and practical experience in big data engineering, analytics, machine learning, or Public Cloud related technologies & their applications.
Product lifecycle experience/area product management experience.
Knowledge of ETL principles or data structures.
Understand demand forecasting methodologies and labor analytics.

Responsibilities

Design strategy and deliver data, analytics, and artificial intelligence solutions that drive measurable business value for sales teams.
Improve sales outcomes by optimizing the sales funnel through analytics, monitoring, and insight generation.
Build data- and artificial intelligence-enabled coaching and enablement capabilities that help managers develop teams effectively.
Deliver personalized insights and meeting preparation experiences that help sales teams better understand and serve clients.
Partner with data owners, data scientists, product, engineering, and business leaders from ideation through deployment and adoption.
Translate business priorities into scalable data, analytics, and artificial intelligence solutions.
Communicate complex technical concepts clearly to executive and non-technical audiences.
Influence senior stakeholders to drive alignment, prioritization, and decision-making.
Accelerate data strategy, data product management, governance, data quality, and measurement practices that support artificial intelligence at scale.
Identify and manage program risks, dependencies, and execution challenges across multiple workstreams.