Koppers Holdings

Director, AI and Data Enablement

Koppers Holdings • $130K — $180K *
Pittsburgh, PA 15237In-Person
Enterprise Technology
Less than 5 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Bachelor's degree in relevant field; Master's preferred.
  • Preferred experience in manufacturing or asset-intensive industries.
  • Proficiency in technology, data analytics, and AI.
  • Experience with enterprise applications (Microsoft, ERP, CRM, etc.) adoption.
  • Expertise in AI adoption and measurable business outcomes.
  • Familiarity with Microsoft Azure, SQL, Python, and related tools preferred.
  • Strong program management and stakeholder engagement skills.

Responsibilities

  • Build enterprise AI and data enablement roadmap focusing on business value.
  • Identify and evaluate AI use cases across various functions through a governance process.
  • Partner with leaders to prioritize AI opportunities aligned with business outcomes.
  • Drive adoption of AI capabilities in existing enterprise platforms.
  • Establish and lead an AI Center of Enablement to support business users.
  • Develop reusable data products and AI-enabled workflows to solve business problems.
  • Measure and communicate outcomes related to productivity and operational efficiencies.

Benefits

  • Opportunities for professional development and training.
  • Collaboration with senior leadership and cross-functional teams.
  • Access to advanced technologies and tools for innovation.
  • Supportive work environment focused on AI and data strategies.
  • Possibility to influence significant business transformation initiatives.
Full Job Description
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.


About Koppers Holdings

Koppers is a global provider of treated wood products, wood treatment chemicals and carbon compounds. The company was founded in 1912 and is headquartered in Pittsburgh, Pennsylvania. Koppers operates in three segments: Railroad and Utility Products and Services, Carbon Materials and Chemicals, and Performance Chemicals. The company's products and services are used in a variety of industries, including railroad, specialty chemical, utility, residential lumber, agriculture, aluminum, steel, rubber, and construction.
Learn more about Koppers Holdings
Size
2,088 employees
Market Cap
$602.8 million
Industry
Business Services
Net Income
$122 million
Founded
1988
5 Year Trend
+3.5%
Revenue
$1.6 billion
NASDAQ
KOP
* Ladders Estimates

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