ZipRecruiter

Log In

1

Vice President Data Science Jobs in Virginia (NOW HIRING)

Virginia Farm Bureau

Vice President, Data & AI

Henrico, VA · On-site

$228K - $240K/yr

Vice President, Data & AI STATUS: Exempt COMPENSATION RANGE: $228,000 - $240,000 Annually with up ... Bachelor's degree in Information Technology, Computer Science, Engineering, Data Science, or a ...

New

Centerline

Vice President Data Center

Richmond, VA · On-site +1

The Vice President(VP), - Data Center Services(DCS) will play a key leadership role in ensuring the successful sourcing and delivery of complex infrastructure projects within the data center ...

Surescripts

VP Data Solutions

Arlington, VA · On-site

The VP Data Solutions drives cross-functional alignment and ensures the portfolio delivers ... Experience with Life Sciences customers, including commercialization of data products in that ...

H5 Data Centers

VP of Operations

Ashburn, VA · On-site

$180K - $230K/yr

As the VP of Operations for our colocation data centers, you will play a pivotal role in overseeing ... Bachelor's degree in computer science, Engineering, Business Administration, or other related field ...

next page

Showing results 1-20

All JobsVice President Data Science JobsVice President Data Science Jobs in Virginia

Vice President Data Science information

See Virginia salary details

$43.1K

$156.2K

$275.1K

How much do vice president data science jobs pay per year?

As of Aug 8, 2026, the average yearly pay for vice president data science in Virginia is $156,181.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,000.00 and $188,400.00 per year, depending on experience, location, and employer.

What are some common challenges faced by a vice president of data science when scaling data teams across an organization?

A Vice President of Data Science often encounters challenges such as aligning data initiatives with business objectives, ensuring consistent data governance practices, and fostering effective collaboration between technical and non-technical teams. Balancing the need for rapid innovation with maintaining data quality and compliance can also be demanding. Additionally, scaling the team requires strong leadership skills to recruit, mentor, and retain top talent while promoting a culture of knowledge sharing and continuous learning.

What is the difference between Vice President Data Science vs Data Scientist?

AspectVice President Data ScienceData Scientist
Required CredentialsAdvanced degrees (Master's/PhD), leadership experienceBachelor's or Master's in relevant field
Work EnvironmentExecutive leadership, strategic planningTechnical analysis, model development
Employer & Industry UsageCorporate, large organizations, tech, financeVaried industries, research labs, startups

The Vice President Data Science typically oversees data strategy and manages teams, requiring leadership and strategic skills. Data Scientists focus on building models and analyzing data. While both roles require strong technical skills, the VP role emphasizes management and vision, whereas Data Scientists are more hands-on with data analysis.

What are the key skills and qualifications needed to thrive as a vice president of data science, and why are they important?

To thrive as a Vice President of Data Science, you need deep expertise in statistics, machine learning, and data analytics, typically supported by an advanced degree in a quantitative field and significant leadership experience. Familiarity with data platforms like Hadoop, Spark, and cloud-based analytics tools, as well as experience with programming languages such as Python or R, is crucial, along with certifications in data management or analytics. Strong strategic vision, communication, and team leadership skills distinguish top performers in this role. These skills and qualities drive innovation, enable data-driven decision-making, and ensure alignment with organizational goals.

What does a vice president of data science do?

A Vice President of Data Science leads the data science division within an organization, overseeing teams that analyze large datasets to drive strategic business decisions. They are responsible for developing data-driven strategies, managing data science projects, and ensuring the alignment of analytics initiatives with the company’s goals. This executive role also involves collaborating with other leaders, mentoring data science teams, and staying updated on the latest technologies and trends in data science. Ultimately, the Vice President of Data Science ensures that the organization's data assets are leveraged to create measurable business value.

What does a vice president of data science do?

As vice president of data science, your responsibilities include targeting audiences through both online and offline data. You lead a team of analysts, manage client needs, and implement solutions to build brands. Predictive analytics is a large part of this job, as is the ability to create strong content based on data science. You use analytical data to develop a business model that reaches a broader audience. Other duties include providing thought leadership, anticipating project risks, and translating analytical science into actionable marketing campaigns. This role is almost always in-house.

More about Vice President Data Science jobs
What are the most commonly searched types of Data Science jobs in Virginia? The most popular types of Data Science jobs in Virginia are:
What are popular job titles related to Vice President Data Science jobs in Virginia? For Vice President Data Science jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Vice President Data Science jobs in Virginia look for? The top searched job categories for Vice President Data Science jobs in Virginia are:
What cities in Virginia are hiring for Vice President Data Science jobs? Cities in Virginia with the most Vice President Data Science job openings:
Vice President Data Science jobs near you
Infographic showing various Vice President Data Science job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $156,181 per year, or $75.1 per hour.

Vice President, Data & AI

Virginia Farm Bureau

Henrico, VA • On-site

$228K - $240K/yr

Full-time

Medical, Dental, Retirement, PTO

Posted 3 days ago

New

Virginia Farm Bureau rating

9.4

Company rating: 9.4 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

15th of 303 rated insurance

Job description

POSITION TITLE: Vice President, Data & AI
STATUS: Exempt
COMPENSATION RANGE: $228,000 - $240,000 Annually with up to 20% annual bonus potential
LOCATION: Based out of our beautiful West Creek Office, located at 12580 West Creek Pkwy, Richmond, VA 23238.
REPORTS TO: Chief Technology Officer (CTO)
Position Summary
The Vice President of Data & AI is accountable for establishing, governing, and advancing Virginia Farm Bureau's enterprise data and analytics capabilities through a federated data strategy, while developing responsible artificial intelligence capabilities over time.
This role owns data as a strategic enterprise asset-setting standards, governance, platforms, and guardrails-while enabling business domains to retain ownership and accountability for their data through defined Data Domain Councils and stewardship models. The VP ensures enterprise consistency, trust, and regulatory compliance without centralizing all data delivery or decision-making.
The VP of Data & AI partners closely with executive leadership, Enterprise Architecture, Cybersecurity, and business leaders to ensure data and AI investments deliver measurable value, scale responsibly, and align with Farm Bureau Tech's platform-led operating model.
Key Responsibilities
Federated Data & AI Strategy
  • Define and execute a federated enterprise data and AI strategy that balances centralized standards and platforms with distributed domain ownership.
  • Establish clear enterprise data principles that empower business domains while ensuring enterprise-level trust, security, and interoperability.
  • Act as the executive accountable for data and AI outcomes across the enterprise, regardless of organizational placement.

Enterprise Data Governance & Stewardship
  • Own enterprise data governance frameworks, policies, standards, and oversight mechanisms.
  • Lead Data Governance Councils and domain-based stewardship models that assign clear data ownership within business areas.
  • Ensure consistent data definition, quality, classification, lineage, and lifecycle management across federated data domains.
  • Partner with Audit, Compliance, and Cybersecurity to ensure data practices meet regulatory and legal obligations.

Data Engineering & Shared Platforms
  • Lead enterprise data engineering and platform teams responsible for shared data infrastructure, integration, analytics tooling, and enablement.
  • Provide common, reusable data and analytics platforms that business domains leverage while maintaining ownership of their data products.
  • Ensure enterprise data platforms are scalable, resilient, secure, and aligned with enterprise architecture standards.

Artificial Intelligence Enablement (Federated by Design)
  • Establish enterprise AI governance, standards, and guardrails to support responsible and compliant AI use.
  • Enable business-led AI use cases through shared platforms, tooling, and policies rather than centralized solution ownership.
  • Guide prioritization of AI initiatives that deliver measurable business value and align with data readiness and governance maturity.

Executive Partnership & Enterprise Alignment
  • Serve as a strategic advisor to executive leadership on data, analytics, and AI opportunities, risks, and tradeoffs.
  • Partner closely with the Director, Enterprise Architecture to align data platforms, integration patterns, and AI capabilities with the broader technology ecosystem.
  • Translate complex data and AI topics into actionable guidance for leadership and business stakeholders.

Organization & Talent Leadership
  • Build, lead, and develop high-performing teams across Data Governance, Data Engineering, and AI functions.
  • Enable success of federated, business-embedded data resources through standards, coaching, and shared delivery models rather than direct control.
  • Foster a culture of accountability, collaboration, and enterprise-first thinking across centralized and federated teams.

Required Qualifications
  • Bachelor's degree in Information Technology, Computer Science, Engineering, Data Science, or a related field; advanced degree preferred or equivalent experience.
  • 12+ years of progressive leadership experience in data, analytics, or technology roles with enterprise-scale responsibility.
  • Demonstrated experience delivering data platforms and governance in a federated or hybrid operating model.
  • Strong understanding of data architecture, analytics platforms, integration patterns, and data security/privacy requirements.
  • Experience operating in regulated environments such as insurance, financial services, or healthcare.
  • Proven ability to influence outcomes across business and technology leaders without relying solely on centralized authority.

Preferred Qualifications
  • Prior experience leading multiple teams or functions across governance, engineering, analytics, or AI.
  • Experience implementing federated data ownership models using councils, stewards, or domain-based accountability structures.
  • Experience establishing or scaling AI capabilities in an enterprise environment.
  • Familiarity with modern data cataloging, lineage, and governance tools used to support federated data strategies.

Key Competencies
  • Executive leadership and enterprise stewardship
  • Strong governance mindset balanced with enablement
  • Systems-level and platform-oriented thinking
  • Ability to influence and align federated teams
  • Translation of data and AI complexity into business value

Success Measures
  • Trusted, well-governed enterprise data assets across domains
  • High adoption of shared data platforms by federated teams
  • Improved data quality, consistency, and transparency enterprise-wide
  • Responsible, business-led AI use cases enabled by enterprise standards
  • Strong alignment between data, architecture, security, and business strategy

BENEFITS OVERVIEW
At VA Farm Bureau, we provide an exceptional benefits package, including ongoing job development and support in all roles, paid training and continuing education reimbursement, medical and dental insurance available on your first day, generous employee 401K contribution, excellent Paid Time off (PTO) plan and more!
Virginia Farm Bureau Companies provide equal employment opportunity in all aspects of employment without regard to race, color, national origin, religion, gender, pregnancy, age, disability, orientation or veteran status.

What Virginia Farm Bureau employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply