Director, AI and Data Enablement

Koppers Inc.•Pittsburgh, PA

20h

About The Position

The Director, AI and Data Enablement will build and scale enterprise artificial intelligence (“AI”), digital capabilities, and a data operating and governance model that enables measurable business impact across Koppers. This role involves developing an enterprise AI and data enablement strategy, driving AI enablement and adoption, fostering business partnerships for value realization, and strengthening data governance and responsible AI practices.

Requirements

Bachelor’s degree in information systems, Computer Science, Data Science, Engineering, Business Analytics, Mathematics, Statistics, or a related field; Master’s degree preferred.
Proficiency in technology, data, analytics, digital transformation, AI, enterprise applications, or related disciplines.
Expertise in enterprise AI adoption, data enablement, analytics, governance, digital transformation, or technology initiatives that delivered measurable business outcomes.
Strong program management, stakeholder management, and change management skills.
Strong understanding of enterprise data management, data governance, AI governance, enterprise applications, security, privacy, and enterprise technology architecture.
Strong knowledge of generative AI, agentic AI, predictive analytics, machine learning concepts, data visualization, and enterprise AI platforms.
Proven ability to communicate complex technical concepts to non-technical audiences.

Nice To Haves

Experience in manufacturing, chemicals, or other asset-intensive industries preferred.
Experience driving adoption of AI capabilities across Microsoft, ERP, CRM, EHS, supply chain, analytics, collaboration, and productivity solutions preferred.
Familiarity with Microsoft Azure AI, Microsoft Copilot, Microsoft Fabric, Power BI, Databricks, Snowflake, Oracle, Salesforce, SQL, Python, or similar technologies preferred.
Familiarity with enterprise data governance, master data management (MDM), and data quality programs preferred.
Familiarity with cloud architecture, APIs, data integration, enterprise architecture, and AI platform ecosystems preferred.
Certification or training in AI, cloud platforms, project management, data governance, cybersecurity, or enterprise architecture preferred.

Responsibilities

Build the enterprise AI and data enablement roadmap, governance structure, and operating model, with a focus on business value and platform-based capabilities.
Identify, prioritize, and evaluate AI and analytics use cases across manufacturing, commercial, supply chain, finance, safety, legal, and corporate functions through a clear intake, governance, and value-assessment process.
Partner with senior leaders to shape the enterprise AI agenda, prioritize the highest-value opportunities, and align investments with strategic business outcomes.
Drive adoption of AI capabilities embedded in existing enterprise platforms, including Microsoft, ERP, EHS, CRM, supply chain, analytics, and related systems.
Identify opportunities to leverage existing enterprise technology capabilities and vendor innovations before pursuing custom AI development.
Establish and lead an AI Center of Enablement that supports business users with education, consultation, governance, and use-case prioritization.
Partner with business and functional leaders to identify practical AI opportunities to improve productivity, safety, quality, cost, customer experience, and operational performance.
Apply product management principles to develop reusable data products, AI-enabled workflows, decision-support tools and scalable capabilities to solve business problems.
Develop communication, training, and change management strategies that drive successful adoption of AI technologies and data-driven decision making.
Measure and communicate outcomes including productivity improvements, cost savings, revenue opportunities, risk reduction, quality improvements, and operational efficiencies.
Partner with business and technology leaders to strengthen enterprise data governance, data quality, master data management (MDM), and data stewardship practices.
Establish standards for data ownership, quality, metadata management, lifecycle management, and governance processes.
Support development of reusable data assets and enterprise data capabilities that improve scalability of AI and analytics initiatives.
Collaborate with enterprise architecture, data platforms, and application teams to ensure data platforms support enterprise AI and analytics objectives.
Support the development and execution of enterprise data strategies that improve accessibility, quality, consistency, and business value.
Establish responsible AI standards, controls, and governance in partnership with Legal, Cybersecurity, Compliance, HR, Internal Audit, and business leadership.
Maintain governance and approval processes for AI use cases, third-party AI solutions, and emerging technologies.
Monitor evolving AI regulations, industry trends, and emerging risks and incorporate them into enterprise governance practices.