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Avp Data Science Jobs in Ohio (NOW HIRING)

CareSource

AVP, Data Management

Dayton, OH · On-site +1

The AVP partners closely with Data Strategy & Governance, Data & AI Solutions, Enterprise ... Bachelor's degree in Computer Science, Information Systems, Data Management, Engineering, or a ...

CareSource

AVP, Data Management

Dayton, OH · On-site

$150 - $300/hr

The AVP partners closely with Data Strategy & Governance, Data & AI Solutions, Enterprise ... Bachelor's degree in Computer Science, Information Systems, Data Management, Engineering, or a ...

The Hartford

AVP Applied AI

Columbus, OH · On-site +1

AVP Data Science - GD05AE We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to ...

Synchrony Financial

AVP, Model Validation

Canton, OH · On-site

The AVP, Model Validation is responsible for model validation and ensure they are meeting Model ... Master's degree (or foreign equivalent) in Statistics, Mathematics, Data Science or related ...

CareSource

AVP, Actuarial Science

Dayton, OH · On-site +1

$150K - $300K/yr

The AVP, Actuarial Science, is responsible for driving and supporting company strategy and managing ... data when establishing a salary level. In addition to base compensation, you may qualify for a ...

CareSource

AVP, Actuarial Science

Dayton, OH · On-site +1

$150K - $300K/yr

The AVP, Actuarial Science, is responsible for driving and supporting company strategy and managing ... data when establishing a salary level. In addition to base compensation, you may qualify for a ...

CareSource

AVP, Actuarial Science (Medicaid)

Dayton, OH · On-site +1

$150K - $300K/yr

The AVP, Actuarial Science, is responsible for driving and supporting company strategy and managing ... data when establishing a salary level. In addition to base compensation, you may qualify for a ...

Bath & Body Works

AVP, Loyalty & CRM

Reynoldsburg, OH

$178K - $235K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

The AVP, Loyalty & CRM owns one of the most valuable assets in specialty retail: a loyalty program ... Partner with Technology and Data Science to advance the MarTech stack (CDP, orchestration ...

Bath & Body Works

AVP, Loyalty & CRM

Reynoldsburg, OH

$178K - $235K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

The AVP, Loyalty & CRM owns one of the most valuable assets in specialty retail: a loyalty program ... Partner with Technology and Data Science to advance the MarTech stack (CDP, orchestration ...

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Showing results 1-20

All JobsAvp Data Science JobsAvp Data Science Jobs in Ohio

Avp Data Science information

See Ohio salary details

$35.7K

$116.7K

$186.8K

How much do avp data science jobs pay per year?

As of Aug 15, 2026, the average yearly pay for avp data science in Ohio is $116,687.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,600.00 and $129,300.00 per year, depending on experience, location, and employer.

What are some common challenges faced by an AVP of Data Science when aligning data initiatives with business goals?

As an AVP of Data Science, one of the key challenges is ensuring that complex data projects remain closely aligned with evolving business objectives. Balancing technical innovation with practical, actionable outcomes often requires clear communication between data teams and business stakeholders. Navigating organizational silos, managing competing priorities, and translating analytical findings into business impact are critical components of the role. Successful AVPs frequently foster cross-functional collaboration and maintain a strategic perspective to maximize the value of data-driven initiatives.

What does an AVP of Data Science do?

An AVP (Assistant Vice President) of Data Science leads data science teams and projects within an organization, typically overseeing the development of data-driven solutions to support business objectives. They are responsible for setting the strategy for data analysis, managing team members, collaborating with stakeholders, and ensuring high-quality delivery of analytics and machine learning initiatives. The AVP also plays a key role in identifying opportunities to leverage data for business growth, implementing best practices, and staying updated on the latest technologies in data science.

What is the difference between Avp Data Science vs Data Scientist?

AspectAvp Data ScienceData Scientist
Required CredentialsAdvanced degree (Master's/PhD), experience in leadership rolesBachelor's or Master's in relevant field, some experience
Work EnvironmentStrategic, managerial, cross-departmental collaborationHands-on data analysis, model development, coding
Employer & Industry UsageFinancial services, tech, consulting firms, often in leadershipTech companies, startups, research institutions
Common Search & ComparisonHigher-level strategic role, leadership focusTechnical, analytical role, implementation focus

In summary, an Avp Data Science typically holds a senior leadership position with strategic responsibilities and requires advanced credentials, whereas a Data Scientist is more focused on technical analysis and model development. The roles differ mainly in scope, experience, and level of responsibility within organizations.

What are the key skills and qualifications needed to thrive as an AVP Data Science?

To thrive as an AVP Data Science, you need advanced expertise in statistics, machine learning, and data analysis, typically supported by a master’s or PhD in a quantitative field and several years of relevant experience. Familiarity with programming languages like Python or R, big data platforms (e.g., Hadoop, Spark), and experience with data visualization tools and cloud technologies are commonly required. Strong leadership, strategic thinking, and communication skills set top candidates apart by enabling them to guide teams and explain complex findings to stakeholders. These skills and qualities are crucial for driving data-driven decision-making and delivering business value through analytics.

What are popular job titles related to Avp Data Science jobs in Ohio?

For Avp Data Science jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Avp Data Science jobs in Ohio look for?

The top searched job categories for Avp Data Science jobs in Ohio are:

Avp Data Science jobs near you

AVP, Data Management

CareSource

Dayton, OH • On-site, Remote

Full-time

Posted 10 days ago

CareSource rating

7.7

Company rating: 7.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

204th of 308 rated insurance

Job description

Job Summary:
The Associate Vice President, Data Management is a senior technology executive responsible for the strategy, architecture, engineering, integration, quality, and operational management of enterprise data platforms. This leader ensures that the data ecosystem is scalable, secure, reliable, and capable of supporting analytics, artificial intelligence, operational reporting, regulatory compliance, and business transformation initiatives. They serve as the enterprise owner for a modern data platform strategy, including cloud data platforms, data movement, integration architecture, master data management, operational excellence, and data reliability. The AVP partners closely with Data Strategy & Governance, Data & AI Solutions, Enterprise Architecture, Clinical Operations, Finance, and Technology leaders to ensure the enterprise data foundation enables business outcomes while maintaining appropriate controls, performance, and scalability.
Essential Functions:
  • Define and execute the enterprise data platform strategy and multi-year technology roadmap.
  • Establish architecture standards, design principles, and engineering practices supporting enterprise data initiatives.
  • Lead modernization efforts across data platforms, integration technologies, and operational processes.
  • Evaluate emerging technologies and industry trends to continuously improve enterprise data capabilities.
  • Align data platform investments with organizational priorities, technology strategy, and business objectives.
  • Act as executive sponsor for major enterprise data transformation initiatives.
  • Lead the creation and governance of enterprise data architecture standards and reference architectures.
  • Establish target-state architecture supporting operational reporting, advanced analytics, AI, interoperability, and regulatory requirements.
  • Define canonical data models, integration patterns, and enterprise information architecture.
  • Partner with Enterprise Architecture to align data strategy with broader application and infrastructure roadmaps.
  • Oversee metadata-driven architecture, data lineage, and data lifecycle management practices.
  • Drive adoption of modern architectural patterns including lakehouse, event-driven, and domain-oriented data architectures.
  • Provide executive leadership for enterprise data engineering teams.
  • Oversee design, development, and optimization of scalable ETL/ELT pipelines and data products.
  • Ensure engineering delivery practices support reliability, performance, maintainability, and reusability.
  • Champion automation, DevOps, and DataOps capabilities across the organization.
  • Establish engineering standards, code quality practices, CI/CD frameworks, and operational controls.
  • Lead platform optimization efforts to improve performance, scalability, and cost efficiency.
  • Own enterprise integration strategy across clinical, operational, financial, and third-party systems.
  • Ensure integration solutions align with enterprise standards, regulatory requirements, and business objectives.
  • Partner with application and infrastructure teams to streamline system connectivity and data flow.
  • Lead large-scale migration and consolidation initiatives during mergers, acquisitions, or platform modernization efforts.
  • Establish operational governance and performance management practices for data platforms.
  • Ensure platform availability, reliability, resiliency, and service performance meet defined SLAs.
  • Lead enterprise data quality monitoring, remediation, and continuous improvement efforts.
  • Develop operational metrics, KPIs, dashboards, and reporting frameworks to measure platform health and business value.
  • Oversee capacity planning, incident management, root-cause analysis, and problem resolution processes.
  • Partner with Data Strategy & Governance leadership to operationalize data quality standards and stewardship practices.
  • Ensure appropriate security, access controls, disaster recovery, and risk management processes are in place.
  • Build and lead high-performing teams including directors, managers, architects, engineers, and operations professionals.
  • Foster a culture of accountability, innovation, operational excellence, and continuous improvement.
  • Develop leadership talent and succession planning within the organization.
  • Establish organizational priorities, objectives, and performance expectations.
  • Lead vendor management, contract negotiations, and strategic technology partnerships.
  • Manage budgets for personnel, infrastructure, licensing, and external services.
  • Perform any other job related duties as requested.

Education and Experience:
  • Bachelor's degree in Computer Science, Information Systems, Data Management, Engineering, or a related field required
  • Master's degree preferred
  • Equivalent years of relevant work experience may be accepted in lieu of required education
  • Twelve (12) years of progressive experience in data management, data architecture, data engineering, or platform engineering required
  • Five (5) years of leadership experience managing large-scale technology organizations required
  • Experience leading enterprise data platforms supporting analytics, operational reporting, and AI initiatives required
  • Experience establishing and scaling operational practices for mission-critical data platforms required
  • Experience leading cloud-based data modernization initiatives required
Competencies, Knowledge and Skills:
  • Familiarity with healthcare payer industry strongly preferred
  • Knowledge of Databricks, Azure, Snowflake, or comparable modern cloud data platforms
  • Familiarity with data mesh, domain-driven architecture, and modern DataOps practices
  • Familiarity with healthcare interoperability standards including FHIR, HL7, EDI, and related healthcare data exchanges
  • Ability to support AI/ML platforms and large-scale enterprise analytics environments
  • Skilled with master data management, metadata management, and data observability solutions
Licensure and Certification:
  • None
Working Conditions:
  • General office environment; may be required to sit or stand for extended periods of time
  • Travel is not typically required

Compensation range $150,000-$300,000. CareSource takes into consideration a combination of a candidate's education, training, and experience as well as the position's scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee's total well-being and offer a substantial and comprehensive total rewards package.
Compensation Type (hourly/salary):
Salary
Organization Level Competencies
  • Fostering a Collaborative Workplace Culture
  • Cultivate Partnerships
  • Develop Self and Others
  • Drive Execution
  • Energize and Inspire the Organization
  • Influence Others
  • Pursue Personal Excellence
  • Understand the Business

This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.
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