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Vp Of Data Science Jobs (NOW HIRING)

Strive Health

VP, Data Platform

Denver, CO · On-site

The Vice President of Data will ensure that data is transformed into trusted, reusable, and well-documented data products for Digital Product, Software Engineering, Data Science, Analytics, Medical ...

New

Hewlett Packard Enterprise Development LP

$224 - $493/hr

VP, Decision Sciences This role has been designed as 'Hybrid' with a requirement that you will work ... and data science. * Driving strategic goals of the organization to successful completion:

New

Chubb

SVP, PRS - Data Science

Whitehouse Station, NJ · On-site

Responsibilities: As part of the North America Data & Analytics leadership team you will be ... A. and to the EVP, PRS Finance Product and Analytics Officer. As the SVP Data Scientist for ...

Blend360

VP, Finance

Columbia, MD

... power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend ... Our new VP will serve as primary business partner to the NA leader and own the financial narrative ...

Blend360

VP, Finance

Columbia, MD

... power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend ... Our new VP will serve as primary business partner to the NA leader and own the financial narrative ...

The Knot Worldwide

VP, Data Science

The VP of Data Science & Analytics will lead experimentation, business intelligence, and advanced analytics across our global two-sided marketplace. This role is accountable for driving measurable ...

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Vp Of Data Science information

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$142.5K

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How much do vp of data science jobs pay per year?

As of Sep 6, 2026, the average yearly pay for vp of data science in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

What does a VP of Data Science do?

A VP of Data Science is a senior executive responsible for leading an organization's data science strategy and teams. They oversee the development and implementation of data-driven solutions, manage data scientists and analysts, and collaborate with other business leaders to leverage data for strategic decision-making. Their role often includes setting the vision for data initiatives, ensuring the use of best practices in analytics and machine learning, and driving innovation through data. Additionally, they are responsible for aligning data science projects with overall business goals and ensuring measurable impact.

What are the key skills and qualifications needed to thrive as a VP of Data Science?

To thrive as a VP of Data Science, you need deep expertise in statistical modeling, machine learning, and data analytics, backed by an advanced degree in a quantitative field and substantial leadership experience. Familiarity with tools such as Python, R, SQL, cloud platforms, and data visualization systems, as well as experience with data governance frameworks, is typically required. Exceptional communication, strategic vision, and the ability to mentor and lead cross-functional teams are vital soft skills in this role. These skills ensure the effective translation of data-driven insights into business strategies and foster innovation and alignment within the organization.

What are some common challenges faced by a VP of Data Science when leading cross-functional teams?

A VP of Data Science often navigates challenges such as aligning data science initiatives with business goals, managing expectations across departments, and fostering effective communication between technical and non-technical stakeholders. Balancing the need for innovation with practical deliverables can be complex, especially when integrating data-driven insights into existing business processes. Successful VPs build strong relationships with product, engineering, and executive teams to ensure that data science projects deliver measurable value and support organizational growth.

What is the difference between Vp Of Data Science vs Data Science Manager?

AspectVp Of Data ScienceData Science Manager
ResponsibilitiesStrategic leadership, setting data science vision, overseeing multiple teamsTeam management, project execution, mentoring data scientists
Required CredentialsAdvanced degrees (Master's/PhD), extensive experience in data science and leadershipRelevant experience in data science, leadership skills, often a master's degree
Work EnvironmentExecutive-level, cross-departmental collaboration, strategic planningOperational, project-focused, team management within data science teams

The Vp Of Data Science holds a senior leadership role focused on strategic direction and organizational impact, while a Data Science Manager concentrates on managing teams and executing projects. Both roles require strong technical backgrounds, but the Vp's scope is broader, involving high-level decision-making and cross-functional collaboration.

How much does a VP of data science make?

A VP of Data Science typically earns between $150,000 and $250,000 annually, with total compensation often including bonuses and stock options. Salaries vary based on company size, industry, location, and experience, and the role requires strong leadership, advanced analytics skills, and experience with data tools and teams.
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Vp Of Data Science jobs near you
Infographic showing various Vp Of Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.

VP, Data Platform

Strive Health

Denver, CO • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New

Job description

How You'll Make An Impact
At Strive Health, patients come first. We're on a mission to transform chronic conditions by identifying risk earlier, coordinating thoughtful care, and supporting people through every stage of their health journey.
Our work reduces emergency visits, improves outcomes, and helps patients live fuller lives. You'll work alongside passionate Strivers who care deeply about making an impact, show up for one another as One Team, and find ways to elevate the everyday.
If you're looking for meaningful work where your contributions truly matter, you'll feel right at home at Strive!
Benefits & Perks
  • Hybrid-Remote Flexibility -Work from home while fulfilling in-person needs at the office, clinic, or patient home visits.
  • Comprehensive Benefits - Medical, dental, and vision insurance, employee assistance programs, employer-paid and voluntary life and disability insurance, plus health and flexible spending accounts.
  • Financial & Retirement Support - Competitive compensation with a performance-based bonus program, 401k with employer match, and financial wellness resources.
  • Time Off & Leave - Paid holidays, vacation time, sick time, and paid birthgiving, bonding, sabbatical, and living donor leaves.
  • Wellness & Growth - Family forming services through Maven Maternity at no cost and physical wellness perks, mental health support, and an annual professional development stipend.

To learn more about our offerings, click here.
What You'll Do
We are seeking a Vice President of Data Platform to lead Strive's enterprise data platform, data architecture, and data governance capabilities. This leader will carry end-to-end accountability for the design, management, reliability, and evolution of Strive's data warehouse and for ensuring that high-quality, well-governed data is available to the teams that depend on it.
The role will oversee the ingestion and hydration of the warehouse from a broad range of inbound data streams, including health plan (claims, revenue, benchmarks, adjustment, risk adjustment files), clinical, eligibility, pharmacy, laboratory, Admit, Discharge, Transfer (ADT), partner, and operational data. The Vice President of Data will ensure that data is transformed into trusted, reusable, and well-documented data products for Digital Product, Software Engineering, Data Science, Analytics, Medical Economics, Actuarial, Finance, Clinical, and Operations teams.
As a key member of the Technology leadership team, this leader will help establish data as a durable enterprise capability and a strategic foundation for clinical excellence, operational performance, artificial intelligence (AI), and value-based care.
We are looking for a candidate with strong leadership judgment, an entrepreneurial spirit, and excitement for building and scaling a trusted, enterprise data capability in a complex, mission-driven health-tech environment.
Essential Functions
  • Own the vision, strategy, architecture, operating model, and long-term roadmap for Strive's enterprise data warehouse and related data platform capabilities.
  • Carry end-to-end accountability for the routine operation, production support, reliability, and maintenance of warehouse ingestion and hydration across claims, clinical, eligibility, pharmacy, laboratory, ADT, partner electronic health record (EHR), financial, and operational data sources.
  • Establish scalable ingestion, transformation, orchestration, and data-modeling patterns-including batch, incremental, change-data-capture, and streaming approaches-with appropriate attention to latency, cost, resiliency, recoverability, and supportability.
  • Build and operationalize scalable processes that enable Analytics, Data Science, and Medical Economics teams to develop trusted metrics, reporting, and insights in the data warehouse.
  • Establish optimization and efficiency practices that keep the warehouse running quickly and reliably for analytical workloads, and implement governance to identify, retire, and document outdated or redundant metrics.
  • Lead Strive's standard data governance initiatives and ensure that all teams follow consistent protocols across the warehouse.
  • Design and operate a production observability and alerting model for ingestion, transformation, warehouse loads, dependencies, and downstream data products, covering freshness, completeness, volume, schema changes, accuracy, reconciliation, latency, availability, pipeline health, and downstream impact to ensure data quality.
  • Own failed or degraded data-processing incidents from triage through verified closure, including severity assessment, alert routing, escalation, stakeholder communication, recovery, reruns, reprocessing, root-cause analysis, corrective actions, and improvements to mean time to detect and mean time to resolve.
  • Establish and lead a durable data governance and quality-management process, including ownership, stewardship, data contracts, definitions, lineage, access, retention, prioritization, automated validation, reconciliation, anomaly detection, and issue resolution.
  • Partner with Digital Product, Software Engineering, Data Science, Analytics, Medical Economics, and Actuarial teams to support reliable downstream consumption and production deployment, monitoring, and lifecycle management of analytical and machine-learning models.
  • Partner with Security, Privacy, Legal, Compliance, Clinical, and Technology leadership to make governed data available through reliable interfaces, application programming interfaces (APIs), events, and other appropriate consumption patterns while protecting Protected Health Information (PHI).
  • Lead remediation of recurring data-quality issues and ingestion technical debt, and define operating metrics for freshness, completeness, accuracy, availability, alert quality, incident recurrence, service-level adherence, and request fulfillment.
  • Recruit, develop, and retain the data organization; establish the right mix of data engineers, data architects, analytics engineers, evaluate and manage vendors, and consultants; and communicate data risks, tradeoffs, priorities, and production health clearly to executive and cross-functional stakeholders.

Minimum Qualifications
  • 10+ years of professional experience in data engineering, data architecture, analytics engineering, or a related discipline, including experience building and operating enterprise-scale data platforms.
  • 8+ years of experience leading technical data teams, including responsibility for hiring, developing, managing, and aligning data engineers, architects, analytics engineers, or related technical professionals.
  • 7+ years of experience designing and evolving a data warehouse, lakehouse, or comparable enterprise data platform serving multiple technical, analytical, and business stakeholders.
  • 5+ years of experience owning production operations for data pipelines and warehouse workloads, including monitoring, observability, alert triage, escalation, recovery, reprocessing, incident response, and preventive remediation.
  • 5+ years of experience integrating complex and heterogeneous data sources, including structured, semi-structured, transactional, clinical, claims, or partner data.
  • 5+ years of experience building governed data models, datasets, marts, semantic layers, or other reusable data products for downstream technical and business consumers.
  • 3+ years of experience establishing or operating data governance and data-quality practices, including ownership, stewardship, lineage, documentation, data definitions, access controls, and issue management.
  • 5+ years of experience partnering with Digital Product, Software Engineering, Data Science, Analytics, Finance, Actuarial, Medical Economics, Clinical, or Operations teams to deliver trusted data products, reporting, measures, or model inputs.
  • Internet Connectivity - Min Speeds: 3.8Mbps/3.0Mbps (up/down): Latency <60 ms.
  • Ability to travel and be on-site to meet business needs.

Preferred Qualifications
  • Experience in healthcare, healthtech, health plans, provider organizations, value-based care, or another regulated environment where data quality, privacy, and auditability materially affect business and clinical outcomes.
  • Experience with healthcare data and interoperability standards, including medical and pharmacy claims, clinical records, lab and ADT data, FHIR,HL7), eligibility, utilization, quality, or risk-adjustment data.
  • Experience working with modern cloud data platforms, relational and distributed data stores, ELT/ETL) frameworks, orchestration tools, APIs, event streams, and change-data-capture patterns.
  • Experience improving data freshness through selective use of near-real-time or streaming architectures where the business value justifies the added complexity and cost.
  • Experience supporting actuarial, medical economics, risk adjustment, quality, financial, or population-health models and reporting.
  • Experience supporting machine-learning or AI systems through reliable feature pipelines, training datasets, inference inputs, monitoring, and data lineage.
  • Experience leading data-platform modernization, technical-debt reduction, source-system consolidation, or migration from fragmented legacy data environments.

About You
  • You communicate clearly and credibly with technical, clinical, operational, and executive audiences, especially when explaining data risk, tradeoffs, incidents, and decisions.
  • You bring high integrity, dependability, sound judgment, and a strong sense of urgency, accountability, and results orientation.
  • You are action-oriented and pragmatic, with the ability to translate broad data strategy into achievable steps, operating mechanisms, and measurable improvements while maintaining appropriate review discipline.
  • You are committed to building a data culture that is rigorous, service-oriented, transparent, and focused on making high-quality data easier to use responsibly.
  • You meet Strive's internet connectivity requirement: minimum speeds of 3.8 Mbps download and 3.0 Mbps upload, with latency below 60 milliseconds.
  • You are able to travel and work onsite as needed to meet business requirements and connect with stakeholders, serve patients, and attend Strive-sponsored team events.

Annual Salary Range: $173,000 - $231,000. This position is also eligible for a target annual bonus of 30%
Final compensation will be determined based on location, experience, and qualifications.
Strive Health is an equal opportunity employer and drug free workplace. At this time Strive Health is unable to provide work visa sponsorship. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. Please apply even if you feel you do not meet all qualifications. If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to talentacquisition@strivehealth.com.
We do not accept unsolicited resumes from outside recruiters/placement agencies. Strive Health will not pay fees associated with resumes presented through unsolicited means.

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