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Data Implementation Manager Jobs in Ohio (NOW HIRING)

... support of voice, data, security, and audio and visual systems.Design engineered drawings ... Manage the production of network devices and network architecture design and develop all supporting ...

Implementation Coordinator

Wilmington, OH · On-site

$25.72 - $32.60/hr

Overview Implementation Coordinator Working under supervision of the Manager, SEG referring ... manage their warehouse inventory, equip their workforce, or secure their data, we make it happen.

... the Implementation Coordinator, TIDC performs departmental project management activities as ... manage their warehouse inventory, equip their workforce, or secure their data, we make it happen.

Showing results 21-40

Data Implementation Manager information

What are the key skills and qualifications needed to thrive as a data implementation manager, and why are they important?

To thrive as a Data Implementation Manager, you need strong project management abilities, expertise in data integration processes, and a background in information systems or a related field. Familiarity with ETL tools, data warehousing platforms, and certifications like PMP or Six Sigma are commonly required. Exceptional communication, problem-solving, and stakeholder management skills help you coordinate teams and manage client expectations. These competencies ensure data solutions are delivered accurately, efficiently, and aligned with business needs.

What are the most common challenges faced by data implementation managers during client onboarding, and how can they be effectively addressed?

Data Implementation Managers often encounter challenges such as integrating disparate data sources, managing client expectations regarding project timelines, and ensuring data accuracy during migration. To address these, it is crucial to establish clear communication channels with clients, set realistic milestones, and conduct thorough data validation checks. Collaborating closely with technical teams and stakeholders helps proactively identify issues and ensure a smooth onboarding process.

What is a data implementation manager?

A Data Implementation Manager is responsible for overseeing the deployment and integration of data solutions within an organization. They work closely with clients, technical teams, and stakeholders to ensure data systems are installed, configured, and operating according to business requirements. Their role includes managing project timelines, troubleshooting issues, and providing guidance on best practices for data migration and utilization. Data Implementation Managers play a key role in aligning technology solutions with organizational goals, ensuring data accuracy, and optimizing workflows.

What is the difference between Data Implementation Manager vs Data Analyst?

AspectData Implementation ManagerData Analyst
Required CredentialsBachelor's in IT, Data Science, or related field; certifications like PMP or data management certificationsBachelor's in Statistics, Data Science, or related field; certifications like Microsoft Excel, Tableau, or SQL
Work EnvironmentProject-based, cross-departmental teams, focus on data system deploymentData-focused, analytical tasks, reporting, and visualization
Employer & Industry UsageUsed in tech, finance, healthcare for data system rolloutsCommon across industries for data analysis and reporting

The Data Implementation Manager primarily oversees the deployment and integration of data systems within organizations, focusing on project management and technical coordination. In contrast, a Data Analyst concentrates on analyzing data to generate insights, reports, and visualizations. While both roles require data-related skills, the Implementation Manager emphasizes system deployment, whereas the Analyst emphasizes data interpretation and reporting.

What are popular job titles related to Data Implementation Manager jobs in Ohio? For Data Implementation Manager jobs in Ohio, the most frequently searched job titles are:
What cities in Ohio are hiring for Data Implementation Manager jobs? Cities in Ohio with the most Data Implementation Manager job openings:

AI Implementation & Project Manager

CEO's Corner

Cincinnati, OH

Other

Posted 13 days ago


Job description

SCOPE: The AI Implementation & Project Manager will lead organizational efforts to adopt, integrate, and scale artificial intelligence solutions across departments. This role will work closely with department leadership to identify operational bottlenecks, analyze current workflows and future needs, design AI-enabled improvements, and oversee projects from concept through full deployment. The position requires strong cross-functional communication skills, a solid understanding of AI technologies, and the ability to quantify outcomes such as cost savings, productivity gains, and time reduction. This role also supports change management, adoption planning and post-implementation evaluation to ensure solutions are sustained over time.

ESSENTIAL DUTIES AND RESPONSIBILITIES: The below statements are intended to describe the general nature and scope of work being performed by this position. This is not a complete listing of all responsibilities, duties and/or skills required.

AI Strategy & Planning:

Meet regularly with department leaders to understand workflows, challenges, and opportunities where AI can enhance efficiency and productivity.

Develop an agency-wide AI roadmap aligned with organizational goals, compliance requirements, budgetary constraints and operational needs.

Identify and prioritize high-impact AI use cases across departments.

Evaluate current state and future state process to determine where AI can provide measurable value.

Project Management:

Create detailed AI project plans including scope, timelines, milestones, resourcing, budgets and risk mitigation strategies.

Manage implementation from pilot through full deployment, ensuring projects stay on schedule, budgets and within scope.

Coordinate with IT, vendors, and stakeholders to ensure technology readiness, policy alignment, and successful adoption.

Track action items, dependencies, and deliverables through implementation and post launch optimization.

AI Implementation & Support:

Evaluate different types of AI tools (generative AI, automation platforms, predictive analytics, workflow tools, etc.) to determine the best fit for specific departmental needs.

Assist teams in adopting AI workflows through demonstrations, training, documentation, and ongoing support.

Develop standards, best practices, and governance guidelines to promote safe, responsible, and compliant AI use.

Develop user guides, process maps, standard operating procedures, and best practice documentation to support consistent use.

Provide ongoing support after deployment to improve adoption and resolve issues.

Change Management & Adoption:

Lead change management efforts to encourage adoption of new AI tools and processes.

Partner with leaders and frontline staff to address resistance, gather feedback, and improve implementation outcomes.

Develop communication and training strategies tailored to different user groups and skill levels.

Monitor adoption rates and user engagement and recommend additional support where needed.

Governance, Privacy & Compliance:

Help develop and enforce AI governance policies, SOPs, guidelines, acceptable use standards, and internal control practices.

Ensure AI solutions comply with privacy, security, records retention, and regulatory requirements.

Set up AI employee usage monitoring systems and reports for risk management to ensure AI policy, procedures and guidelines adherence.

Work with IT, legal, and leadership teams to assess risk and establish approval processes as needed.

Document data handling practices and ensure sensitive information is protected appropriately.

Data & Outcome Measurement:

Design and track key metrics to quantify results such as time saved, cost reduction, performance improvements, accuracy gains, and productivity impacts.

Prepare clear reports and presentations for executive leadership showing ROI, operational benefits, and progress toward agency AI maturity.

Conduct post-implementation reviews to evaluate results and identify opportunities for improvement.

Use data to support continuous improvement and future AI planning.

Perform additional duties as assigned.