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Assistant Data Governance Jobs in Ohio (NOW HIRING)

The VP of Data, Analytics and AI also plays a leading role in building data governance and analytics infrastructure supporting Premier's Wright State University academic partnership and Academic ...

The VP of Data, Analytics and AI also plays a leading role in building data governance and analytics infrastructure supporting Premier's Wright State University academic partnership and Academic ...

The VP of Data, Analytics and AI also plays a leading role in building data governance and analytics infrastructure supporting Premier's Wright State University academic partnership and Academic ...

The VP of Data, Analytics and AI also plays a leading role in building data governance and analytics infrastructure supporting Premier's Wright State University academic partnership and Academic ...

Senior Data Scientist

Cleveland, OH · On-site

$120 - $180/hr

... governance and compliance standards. DUTIES & RESPONSIBILITIES * Design and implement ... Build and deploy LLM‑powered applications, such as enterprise knowledge assistants and chatbots

... knowledge assistants, document processing systems, and workflow automation tools. The ideal ... governance and compliance standards. DUTIES & RESPONSIBILITIES Design and implement enterprise ...

Senior Data Scientist

Cleveland, OH · On-site

$120 - $190/hr

Build and deploy LLM-powered applications, such as enterprise knowledge assistants and chatbots ... Ensure compliance with enterprise data governance, privacy, and security standards * Support model ...

... governance practices. In partnership with business stakeholders and third-party vendors, the Data ... Lead and assist in administration, optimization, and operational oversight of Snowflake and related ...

... governance practices. In partnership with business stakeholders and third-party vendors, the Data ... Lead and assist in administration, optimization, and operational oversight of Snowflake and related ...

... governance practices. In partnership with business stakeholders and third-party vendors, the Data ... Lead and assist in administration, optimization, and operational oversight of Snowflake and related ...

... knowledge assistants, document processing systems, and workflow automation tools. The ideal ... AI solutions that align with enterprise governance and compliance standards. DUTIES ...

Showing results 21-40

Assistant Data Governance information

What is the difference between Assistant Data Governance vs Data Analyst?

AspectAssistant Data GovernanceData Analyst
Required CredentialsCertifications in data management, data governance frameworksDegree in statistics, data science, or related field
Work EnvironmentCorporate data teams, compliance departmentsBusiness units, analytics teams
Employer & Industry UsageFinancial, healthcare, tech companiesMarketing, finance, consulting firms
Common Search & ComparisonOften compared for data management rolesMore focused on data analysis and insights

Assistant Data Governance focuses on implementing data policies, ensuring data quality, and maintaining compliance within organizations. Data Analysts primarily analyze data to generate reports, insights, and support decision-making. While both roles work with data, Assistant Data Governance emphasizes data integrity and governance frameworks, whereas Data Analysts focus on data interpretation and visualization.

What are the main responsibilities of an assistant data governance professional?

As an Assistant Data Governance professional, your primary responsibilities include supporting data stewardship activities, maintaining data quality standards, assisting in policy documentation, and monitoring data compliance. You will often collaborate with data owners, IT teams, and business stakeholders to ensure that data is accurate, secure, and used appropriately. This role is crucial in helping the organization adhere to data governance frameworks and regulatory requirements, and it provides a solid foundation for advancing into more senior data management roles.

What are the key skills and qualifications needed to thrive as an assistant data governance professional?

To thrive as an Assistant Data Governance professional, you need a foundational understanding of data management principles, data quality standards, and relevant regulations, often supported by a degree in information management or a related field. Familiarity with data governance tools, data cataloging systems, and knowledge of frameworks like DAMA-DMBOK or GDPR compliance certifications is advantageous. Strong attention to detail, effective communication, and problem-solving skills help you collaborate across departments and enforce data policies. These skills are crucial for maintaining high data quality, regulatory compliance, and enabling informed decision-making within an organization.

What is an assistant data governance?

Assistant Data Governance roles involve supporting the implementation and maintenance of data governance policies and procedures within an organization. People in this position help ensure data quality, security, and compliance by assisting with data management tasks, monitoring data usage, and documenting data-related processes. They often collaborate with data stewards, IT teams, and business units to promote best practices and uphold data standards. This role may also include assisting with audits, reporting, and the resolution of data-related issues.

What are the most commonly searched types of Data Governance jobs in Ohio?

The most popular types of Data Governance jobs in Ohio are:

What are popular job titles related to Assistant Data Governance jobs in Ohio?

For Assistant Data Governance jobs in Ohio, the most frequently searched job titles are:

What cities in Ohio are hiring for Assistant Data Governance jobs?

Cities in Ohio with the most Assistant Data Governance job openings:

VP-DATA/ANALYTICS & AI

Premier Health

Dayton, OH • On-site

Full-time

Posted 15 days ago


Job description

The VP of Data, Analytics and AI is an executive leadership role responsible for leveraging data, analytics, and artificial intelligence to drive business and clinical value, foster a data-driven culture, and ensure effective governance and use of Premier's data assets and ecosystem. Reporting to the Chief Digital Information Officer (CDIO), the VP of Data, Analytics and AI leads the execution of Premier's enterprise data, analytics, and AI strategy and operating model, builds executive and Board-level trust in data as a strategic asset; operationalizes enterprise data governance in partnership with security, privacy, risk, and compliance leaders; and develops the talent and culture required to mature Premier's data and analytics capability.  This role will partner with senior leaders across Premier Health to understand their data needs and deliver tools to enable them to achieve their business, clinical and operational initiatives.

As a member of the DHT senior leadership team, the VP of Data, Analytics and AI leads day-to-day strategy execution, operating model design, and delivery for the data, analytics, and AI portfolio.  This role will work in close coordination with the CDIO's technology infrastructure, Epic platform governance, and cybersecurity functions to ensure a single, unified digital agenda to support the strategic initiatives of Premier Health.  The VP of Data, Analytics and AI also plays a leading role in building data governance and analytics infrastructure supporting Premier's Wright State University academic partnership and Academic Medical Center designation, consistent with priorities set by the organization.

Education: Bachelor's Degree in Business Administration, Computer Science, Data Science, Information Systems, Health Informatics, or a related field. Master's degree (e.g., MBA, MS Data Science, MS Health Informatics) preferred.

Licensure/Certification/Registration: None required; Certified Analytics Professional (CAP) or comparable data/AI governance certification preferred.

Experience: Minimum 10 to 15 years of progressive business experience, recently at or near the executive level such as Senior data, analytics, or business intelligence executive (e.g., VP/SVP Data & Analytics, Chief Analytics Officer, Chief AI Officer) with progressive leadership experience required. Must have experience with enterprise data & analytics strategy, data governance, AI enablement, and cross-functional program leadership. Preferred experience: Healthcare or health system experience; academic medical center or university-affiliated data governance experience; strategy or management consulting background.
Other experience requirements: 5 or more years of progressive leadership managing cross-functional, multidisciplinary data and analytics teams across a complex organization.

Knowledge/Skills:
      Enterprise data, analytics, and AI strategy development and execution, including policy development
      Data and analytics governance (master data management, data quality, data stewardship) and connected governance with privacy, security, and compliance functions
      Broad understanding of information architectures (data fabric, data mesh, data warehouse, data lake, data hub) and analytics approaches (descriptive, diagnostic, predictive, prescriptive)
      AI fundamentals, including AI-ready data practices, responsible/ethical AI use, and awareness of applicable healthcare regulations (e.g., HIPAA, information blocking rules, emerging state and federal AI regulation)
      Business and financial acumen; ability to translate data, analytics, and AI concepts into business and clinical outcomes and ROI
      Exceptional executive communication, storytelling, and stakeholder influence across clinical, operational, financial, and Board audiences
      Demonstrated leadership building and managing complex, multidisciplinary teams and driving enterprise-wide culture change
      Experience operating within a CIO/CDIO-led digital governance structure, and partnering effectively with CISO, Compliance, and Legal functions on data trust, security, and governance
      Statistical literacy (e.g., understanding the difference between correlation and causation) sufficient to guide analytically rigorous decision-making