What are the responsibilities and job description for the Vice President, Data Architecture, Engineering & AI (Remote) position at KOHLS?
About the Role
As Vice President, Data Architecture, Engineering & AI you will be responsible for driving the vision, strategy, and execution of data products that enable business growth, operational efficiency, and customer-centric innovation. This role partners closely with business and technology leaders to transform data into a strategic asset, delivering scalable, reliable, and user-friendly data solutions.
What You’ll Do
Define and own the data product and technical data science strategy, aligning with enterprise technology and business priorities
Lead the design, development, and lifecycle management of data products that support business operations, customer insights, and innovation
Build and scale data science capabilities, including machine learning, AI-driven solutions, and advanced analytics to optimize retail operations and customer engagement
Partner with business units, analytics, engineering, and product management to prioritize high-value use cases for both data products and data science applications
Oversee data governance, stewardship, and metadata management to ensure accuracy, compliance, and trust
Champion modern data and AI architectures, including cloud-native platforms, APIs, data streaming services, and real-time analytics
Drive data democratization, ensuring business users can easily discover, access, and leverage insights
Foster a product mindset and a research-to-production pipeline for data science solutions, ensuring scalability and usability
Manage, mentor, and grow a high-performing team of data product managers, architects, engineers, and data scientists
Define and monitor KPIs for both data products and data science initiatives, ensuring outcomes translate into tangible business impact
Represent data and AI strategy at the executive level, influencing enterprise decisions and advocating for innovation
Additional tasks may be assigned
What Skills You Have
Required
12 years of experience in data leadership roles, including data product management, data platforms, and data science
Proven track record of building and scaling data products and machine learning/AI solutions in large, complex organizations
Strong expertise in modern data and AI/ML architectures, including cloud platforms (AWS, GCP, or Azure), data lakes/warehouses, and governance frameworks
Exceptional executive communication and stakeholder management skills, with the ability to influence across business and technology functions
Demonstrated success in leading cross-functional teams spanning data science, engineering, and product management