Job Title – Principal Data & AI Governance Analyst
Overview of Providence:
At Providence, we use our voice to advocate for vulnerable populations and needed reforms in health care. We pursue innovative ways to transform health care by keeping people healthy, and making our services more convenient, accessible and
affordable for all. In an increasingly uncertain world, we are committed to high-quality, compassionate health care for everyone—regardless of coverage or ability to pay. We help people and communities’ benefit from the best health care model for the future—today.
Together, our 119,000-plus caregivers/employees serve in 51 hospitals, more than 1000 clinics and a comprehensive range of health and social services across Alaska, California, Montana, New Mexico, Oregon, Texas and Washington in United States.
Providence Information Service (commonly known as Information technology) is aimed to digitally enable our vision of Health for a better world. We make use of multiple technologies spread across Microsoft, Oracle, JAVA, Python and many new open sources.
Providence Global Center recently launched in Hyderabad, India as Global Capability Center for Providence looking to leverage the India talent to help meet our global vision and scale our Information Services and products to the world of Cloud.
About Healthcare Intelligence
Healthcare Intelligence is the pillar that focuses on creating intelligent data products within Providence and provides unique opportunities in Data Engineering, Operations, Data Science, BI Reporting and Data Analytics on cloud stack. We are a group of data professionals who work towards enabling decisions that improve patient and caregiver experience.
About the role
We are looking for a Principal Data & AI Governance Analyst to join our organisation, with demonstrated experience in managing large cross-organizational Data & AI Governance initiatives. Ideal candidates should have a technical background in Data & AI Governance Standards & Frameworks, Data Ownership & Stewardship, Risk Management, Regulatory Change, and various Data Governance tools. They must be able to thrive and succeed in an entrepreneurial environment, and not be hindered by ambiguity or competing priorities. This means not only being able to develop and drive high-level strategic initiatives, but can also roll up their sleeves, dig in and help drive change.
Responsibilities
- Define and drive the enterprise Data & AI Governance strategy, roadmap, operating model, and maturity framework aligned with organizational objectives
- Work with the broader Data & AI team to ensure the continuous roll out of improvements and evolution of compliance controls to ensure the continual maturity of Data & AI Practice.
- Lead AI risk assessments, model risk management reviews, bias and fairness evaluations, explainability assessments, and compliance monitoring.
- Establish and operationalize governance controls across the AIDLC, including intake, approval, development, deployment, monitoring, retraining, and retirement
- Define governance standards for sensitive data protection, data classification, masking, tokenization, encryption, retention, and privacy by design practices
- Monitor evolving AI regulations, healthcare compliance requirements, and industry frameworks (NIST AI RMF, ISO 42001, HIPAA, Responsible AI standards) and recommend governance enhancements.
- Demonstrated experience in oversight and governance of AI/ML models at an enterprise level
- Proven ability to implement, and oversee the governance frameworks and policies
- Investigative skills with the capability to identify key risks and areas of non-conformance with regulatory and legislative requirements and lack of controls, identify root cases, themes, and trends.
- Excellent analytical or and problem-solving skills, proven in complex and dynamic settings
- An innovative mindset, capable of proposing effective solutions to control issues identified
- An in-depth understanding of AI/ML technology including the risks, benefits, ethical implications, and the development of a governance operating model
- A proven track record in AI or governance experience, encompassing business, risk and technical acumen
- Lead adoption of data governance practices including metadata management, data cataloging, data lineage, data classification, data quality management, master data management (MDM), and data stewardship.
- Develop training materials, best practices, and awareness programs related to responsible AI, data privacy, governance policies, and acceptable use of AI technologies.
- Promote transparency, accountability, fairness, and human oversight in AI systems while ensuring alignment with organizational values and patient-centric care principles.
- Ability to work in a high performing team, and the ability to work and liaise with others in a diverse team
- Design and implement data governance to automate data governance processes, monitor data quality, and track data lineage using Industry leading tools such as Microsoft Purview, Databricks Unity Catalog, Collibra, Informatica etc.
- Develop and maintain data dictionaries, data catalogs, and data lineage documentation to provide transparency and visibility into the organization's data assets.
Skills and qualifications
- Bachelor’s/Master’s degree in Information Technology, Computer Science, Data Management, Data Science, Artificial Intelligence, Information Systems, Healthcare Informatics, Engineering, or a related field.
- 7+ years of experience in Data Governance, AI Governance, Risk Management, Compliance, Data Management, or related fields.
- Demonstrated experience supporting enterprise-wide Data Governance and/or AI Governance programs.
- Proven experience implementing and maintaining governance frameworks, policies, standards, and controls.
- Experience overseeing AI/ML models, Generative AI solutions, or advanced analytics initiatives within a regulated industry, preferably healthcare.
- Experience driving adoption of metadata management, data cataloging, data lineage, data quality, data stewardship, and Master Data Management (MDM) practices.
- Experience conducting governance assessments, control reviews, risk evaluations, audits, and compliance monitoring activities.
- Strong understanding of Data Governance principles including metadata management, data cataloging, data lineage, data classification, data quality management, data ownership, and stewardship.
- Knowledge of AI Governance frameworks, Responsible AI principles, model governance, AI risk management, and ethical AI practices.
- Experience with enterprise governance tools such as Microsoft Purview, Collibra, Informatica, Databricks Unity Catalog, or similar platforms.
- Familiarity with cloud-based data platforms and modern data ecosystems including Azure, Databricks, Snowflake, ADLS Gen2, AWS, and related technologies.
- Working knowledge of SQL and data management concepts with the ability to analyze governance-related data and metrics.
- Understanding of AI/ML lifecycle management, model monitoring, explainability, fairness, bias detection, and validation practices.
Preferred Qualifications
- Experience in healthcare, payer, provider, life sciences, or other highly regulated industries.
- Professional certifications such as:
- CDMP (Certified Data Management Professional)
- DCAM (Data Management Capability Assessment Model)
- AI Governance or Responsible AI certifications
- Experience establishing governance operating models for AI and enterprise data management initiatives.
- Knowledge of patient-centric AI governance, ethical AI review processes, and healthcare AI oversight frameworks.
