AI & Data Standards and Enablement Lead

Bausch+Lomb Companies Inc.•Bridgewater, NJ

1d•$125,000 - $155,000•Onsite

About The Position

Bausch + Lomb’s Global Digital and AI organization seeks a passionate and highly motivated AI and Data Standards and Enablement Lead. In this role, you will help scale Bausch + Lomb’s enterprise AI and data agenda responsibly, consistently, and practically by defining enterprise AI policies and standards, leading data governance alignment, operationalizing AI governance and use-case approvals, enabling business adoption, and tracking measurable adoption and governance outcomes. This role will partner closely with Digital, AI, Enterprise Data Products, IT, Legal, Privacy, Security, Compliance, and business stakeholders to embed AI and data governance into day-to-day execution. This role reports to the Head of Enterprise Data Products.

Requirements

Bachelor's degree in Information Systems, Data Management, Analytics, Computer Science, Business, or a related field.
4+ years of experience in AI governance, data governance, data quality, data stewardship, analytics, enterprise enablement, digital transformation, or related disciplines.
Demonstrated experience building, managing, or supporting data governance, data stewardship, data quality, master data management, or data product governance programs.
Strong understanding of Responsible AI principles, including transparency, accountability, privacy, fairness, explainability, human oversight, security, and risk management.
Experience influencing and collaborating across business, technology, legal, privacy, security, compliance, data, and analytics stakeholders.
Proven ability to design governance processes, enablement programs, and metrics-driven adoption strategies that support enterprise transformation initiatives.
Excellent communication, facilitation, and problem-solving skills with the ability to simplify complex concepts for both technical and business audiences.

Nice To Haves

Working knowledge of AI governance frameworks, data governance disciplines, data ownership and stewardship models, RACI structures, metadata management, lineage, data quality controls, data contracts, and access governance.
Experience with AI use-case intake processes, risk assessments, approval workflows, governance documentation standards, and monitoring practices.
Hands-on familiarity with data catalog and governance platforms, including Microsoft Purview preferred; experience with Collibra, Alation, Atlan, or similar tools is a plus.
Ability to develop governance scorecards, dashboards, certifications, adoption metrics, and leadership reporting that measure effectiveness and business value.
Advanced degree in Information Systems, Data Management, Analytics, Computer Science, Business, or a related field.
Experience supporting governance for analytics, machine learning, generative AI, large language models (LLMs), automation, and agentic AI use cases.
Experience in regulated industries such as pharmaceuticals, medical devices, life sciences, healthcare, financial services, or other compliance-focused environments.
Relevant certifications in data governance, data management, analytics, AI governance, or related disciplines.

Responsibilities

Define and operationalize enterprise AI policies, standards, playbooks, templates, and governance practices that support safe, scalable, and responsible AI adoption across the organization.
Lead AI use-case intake, risk assessment, approval workflows, documentation requirements, and compliance monitoring to ensure alignment with enterprise governance expectations.
Partner with data owners, stewards, and Enterprise Data Products teams to establish governance frameworks, certified data product standards, and data lifecycle management practices.
Drive data quality, metadata, lineage, access governance, data contracts, and catalog adoption to improve trust, discoverability, and readiness of governed data assets.
Translate complex AI and data governance requirements into practical toolkits, training materials, decision frameworks, and business-friendly guidance that accelerate adoption.
Develop and execute change management, communications, and stakeholder enablement programs that promote responsible AI practices and governed data usage.
Define, monitor, and report governance KPIs, adoption metrics, certification status, compliance trends, and data quality performance through dashboards and scorecards.
Facilitate governance forums, working groups, and cross-functional decision-making while serving as a trusted advisor to business teams adopting AI and data capabilities.