Manager, Data & AI Governance

AdvanSix plays a critical role in global supply chains, innovating and delivering essential products for our customers in a wide variety of end markets and applications that touch people’s lives, such as building and construction, fertilizers, plastics, solvents, packaging, paints, coatings, adhesives, and electronics. Our reliable and sustainable supply of quality products emerges from the vertically integrated value chain of our three U.S. based manufacturing facilities. AdvanSix strives to deliver best-in-class customer experiences and differentiated products in the industries of nylon solutions, chemical intermediates, and plant nutrients, guided by our core values of Safety, Integrity, Accountability and Respect.

Please view a short video about our company here, AdvanSix Video. For more information on AdvanSix, please visit our website at http://www.advansix.com


Why work at AdvanSix?


• We provide benefits that are industry competitive and focused on employee well-being


• Total Rewards program includes a competitive compensation, health, dental, vision & wellness programs, paid vacation, 401K with company matching, health savings programs, disability & life insurance, employee assistance program


• Tuition reimbursement for continued education, certifications, training, and development


• Work within a fast paced and innovative company, meeting passionate colleagues and partners with diverse backgrounds and experiences


Own AdvanSix’s enterprise Data and AI Governance end to end. Define the operating model with a council and stewards, establish policies for master data management, lineage, quality, and access, ratify the KPI canon, and govern the safe and compliant use of analytics, AI and machine learning, and agentic automation on the Unified Data Platform. Partner with Operations and OT, Finance, Supply Chain and Logistics, HSE and Quality, Commercial, Cyber and IT, and platform teams to turn strategy into measurable, governed outcomes.
Deliver a business outcome driven data and AI governance system that:
• standardizes definitions, lineage, and data quality through master data management and a KPI canon,
• ensures secure, ethical, and compliant analytics and AI through clear policy, risk controls, approvals, and auditability, and
• accelerates adoption by making certified data products and approved AI agents easy to discover and trust.
Responsibilities:
Enterprise data stewardship
• Publish and maintain a living Enterprise Data Governance that links business value such as Yield, Logistics, and Energy to data products, platform patterns, and the operating model, reviewed quarterly with senior leadership.
• Define data product standards including contracts, versioning, slowly changing dimensions handling, documentation, certification criteria, and deprecation rules.
Governance and master data management
• Chair the Data Strategy and Governance Council and stand up a steward network across Operations, Finance, Supply Chain, HSE, Quality, and Commercial.
• Establish policies for quality, lineage, access and privacy using RBAC and RLS, retention, and critical data elements, and implement data quality scorecards with remediation playbooks.
• Prioritize and deliver master data domains with survivorship rules, golden records, and reference data governance.
KPI canon and analytics alignment
• Lead cross functional definition of the KPI canon and reconciliation rules.
• Ensure BI semantic models and agents consume only certified datasets; partner with Reporting and BI on performance SLAs, usage telemetry such as MAU and WAU, and adoption campaigns.
AI and agent governance
• Define risk tiers such as informational, operational, and decision assist, approval workflows, and documentation including model and agent cards.
• Set evaluation standards including offline metrics and controlled pilots, drift monitoring, rollback requirements, and ethics and privacy guidelines for machine learning and Copilot agents.
• Align with the Power Platform Center of Excellence for DLP and ALM so agents and apps use Unified Data Layer APIs and certified datasets rather than uncontrolled sources.
Architecture and risk
• Codify Unified Data Layer first patterns from landing to curated to semantic, OT and IT decoupling with no control network reads, and data sharing agreements with vendors.
• Run risk reviews with Cyber and IT and Legal for data sharing, third party models, and sensitive domains including PII and HSE.
Change management and literacy
• Launch data and AI literacy programs tied to live use cases, publish “How we measure” and “How to act” guides, and host monthly decision reviews that use governed data.
Basic Qualifications:
• Minimum 10 years' experience across data stra