Job Responsibilities
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.
Enterprise AI and Data Enablement Strategy
- 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.
AI Enablement and Adoption
- 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.
Business Partnership and Value Realization
- 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.
Data Governance and Enterprise Data Enablement
- 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.
AI Governance, Risk, and Responsible AI
- 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.
Qualifications
- Bachelor’s degree in information systems, Computer Science, Data Science, Engineering, Business Analytics, Mathematics, Statistics, or a related field; Master’s degree preferred.
- Experience in manufacturing, chemicals, or other asset-intensive industries preferred.
- Proficiency in technology, data, analytics, digital transformation, AI, enterprise applications, or related disciplines.
- Experience driving adoption of AI capabilities across Microsoft, ERP, CRM, EHS, supply chain, analytics, collaboration, and productivity solutions preferred.
- Expertise in enterprise AI adoption, data enablement, analytics, governance, digital transformation, or technology initiatives that delivered measurable business outcomes.
- Familiarity with Microsoft Azure AI, Microsoft Copilot, Microsoft Fabric, Power BI, Databricks, Snowflake, Oracle, Salesforce, SQL, Python, or similar technologies preferred.
- Strong program management, stakeholder management, and change management skills.
- Familiarity with enterprise data governance, master data management (MDM), and data quality programs preferred.
- 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.
- 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.
- Proven ability to communicate complex technical concepts to non-technical audiences.
Koppers Inc. and its subsidiaries are equal opportunity employers. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other category or characteristic protected by federal law, state or local law.
