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Vp Data Science Jobs (NOW HIRING)

Monogram Health

VP Data Science

Position: Vice President, Data Science Reporting to the Chief Technology Officer, the Vice President of Data Science is a senior technology leader responsible for defining and executing the ...

Monogram Health Inc

VP Data Science

Brentwood, TN

Position: Vice President, Data Science Reporting to the Chief Technology Officer, the Vice President of Data Science is a senior technology leader responsible for defining and executing the ...

Coterie Applications, Inc.

VP, Data Science

The VP, Data Science will lead Coterie's data science and research functions within the broader Data and Analytics (DnA) organization. Furthermore, the VP, Data Science will develop and mentor a team ...

Dentsu Aegis Network

VP, Data Science

New York, NY · On-site

$163K - $220K/yr

Role Summary Reports to: EVP, Data Experience Lead Dentsu's measurement and marketing science capability across MMM, RBA, incrementality, forecasting, and market design. You will own the science and ...

Dentsu, Inc.

VP, Data Science

New York, NY · On-site

$163K - $220K/yr

Role Summary Reports to: EVP, Data Experience Lead Dentsu's measurement and marketing science capability across MMM, RBA, incrementality, forecasting, and market design. You will own the science and ...

Chubb

VP, Data Science - Cohort Modeling

Jersey City, NJ · On-site

$163K - $237K/yr

The Vice President, Data Scientist will serve on Chubb's Global Analytics Risk Cohorts team, bringing advanced expertise in pricing modeling, product development, rating architecture, and model ...

New

Chubb

VP, Data Science - Cohort Modeling

Jersey City, NJ

$163K - $237K/yr

The Vice President, Data Scientist will serve on Chubb's Global Analytics Risk Cohorts team, bringing advanced expertise in pricing modeling, product development, rating architecture, and model ...

New

Five9

OR

As Vice President of Data Science, you will lead and grow our in-house data science team. This team is responsible for research, experimentation, data collection and curation, and data analysis that ...

Five9

Vice President, Data Science

As Vice President of Data Science, you will lead and grow our in-house data science team. This team is responsible for research, experimentation, data collection and curation, and data analysis that ...

Five9

Vice President, Data Science

San Ramon, CA · On-site

As Vice President of Data Science, you will lead and grow our in-house data science team. This team is responsible for research, experimentation, data collection and curation, and data analysis that ...

Equation Staffing

VP of Data Science

Manhattan, NY

VP Data Science As the VP of Data Science, you'll play a critical role in building a data-driven culture and driving strategic initiatives. You'll leverage a rich data-set built on a mature data ...

Experian

Learn more at experianplc.com The Senior Vice President, Data Science & Analytics (North America) will have holistic responsibility for all data science and analytics functions of the Financial ...

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All JobsVp Data Science Jobs

Vp Data Science information

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$41.5K

$142.5K

$201K

How much do vp data science jobs pay per year?

As of May 31, 2026, the average yearly pay for vp 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 are the key skills and qualifications needed to thrive as a VP of Data Science, and why are they important?

To thrive as a VP of Data Science, you need advanced expertise in statistical analysis, machine learning, and big data, usually supported by a graduate degree in a quantitative field and extensive industry experience. Familiarity with tools like Python, R, SQL, cloud platforms (e.g., AWS, Azure), and data visualization systems, as well as experience managing enterprise data architectures, is crucial. Exceptional leadership, strategic thinking, and communication skills set top candidates apart in this role. These abilities are essential for guiding teams, influencing business decisions, and driving impactful data-driven strategies across the organization.

How does a VP of Data Science typically collaborate with cross-functional teams to drive business outcomes?

A VP of Data Science frequently works with product managers, engineering teams, and business stakeholders to align data initiatives with organizational goals. They play a strategic role in translating business challenges into data-driven solutions, ensuring that data science projects support decision-making and growth. Effective collaboration involves regular meetings, clear communication of technical concepts to non-technical audiences, and fostering a culture of data literacy across the organization. By bridging technical expertise and business acumen, the VP helps maximize the impact of data science initiatives.

What does a VP of Data Science do?

A VP of Data Science leads and manages the data science team within an organization, setting the strategic vision for how data is used to drive business decisions. They oversee the development and implementation of data-driven solutions, ensure data quality and integrity, and collaborate with other executives to align data initiatives with company goals. Additionally, they mentor data scientists, manage budgets, and stay updated on the latest trends and tools in data science to keep their teams competitive.

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

AspectVp Data ScienceData Science Manager
ResponsibilitiesStrategic leadership, setting data science vision, overseeing multiple teamsManaging data science projects, team supervision, project delivery
Required CredentialsAdvanced degree (Master's/PhD), extensive experience, leadership skillsDegree in related field, experience in managing data projects
Work EnvironmentExecutive-level, cross-departmental collaboration, strategic planningTeam management, project-focused, collaborative with data teams

The Vp Data Science typically holds a strategic, leadership role overseeing multiple teams and setting long-term data initiatives, while a Data Science Manager focuses on managing data projects and teams directly involved in execution. Both roles require strong technical backgrounds, but the Vp is more involved in high-level planning and organizational strategy.

What cities are hiring for Vp Data Science jobs? Cities with the most Vp Data Science job openings:
What are the most commonly searched types of Data Science jobs? The most popular types of Data Science jobs are:
What states have the most Vp Data Science jobs? States with the most job openings for Vp Data Science jobs include:
What job categories do people searching Vp Data Science jobs look for? The top searched job categories for Vp Data Science jobs are:
Vp Data Science jobs near you
Infographic showing various Vp Data Science job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, and 99% Full Time. Highlights an 39% Physical, 55% Hybrid, and 6% Remote job distribution, with an average salary of $142,460 per year, or $68.5 per hour.
VP Data Science

VP Data Science

Monogram Health

Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

Job description

Position: Vice President, Data Science
Reporting to the Chief Technology Officer, the Vice President of Data Science is a senior technology leader responsible for defining and executing the organization's data science and AI strategy. This leader transforms data into actionable insights, drives AI/ML innovation, and partners with operational leadership to influence product direction, operational excellence, and business outcomes. The VP of Data Science builds and leads high-performing teams, establishes scalable data science practices, and ensures models and insights are delivered ethically, reliably, and with measurable business impact.
Responsibilities
Strategic Leadership
  • Define and own the enterprise data science vision, roadmap, and operating model aligned with company strategy.
  • Translate business priorities into high-impact analytics, AI, and machine learning initiatives.
  • Serve as an executive advisor on data-driven decision-making, AI adoption, and emerging technologies.
  • Establish success metrics and ROI measurement for data science initiatives.

Organization Leadership
  • Build, mentor, and scale a diverse, high-performing organization of data scientists and ML engineers.
  • Set clear expectations, career paths, and performance standards.
  • Foster a culture of curiosity, rigor, and collaboration.
  • Create an environment where teams are empowered, accountable, and closely connected to the business.

Delivery AI and Machine Learning
  • Oversee the design, development, deployment, and lifecycle management of predictive and prescriptive models.
  • Ensure solutions are production-grade, integrated into applications and workflows, and supported by strong MLOps practices.
  • Partner with engineering teams to embed models into clinical and operational systems.
  • Establish governance, validation, and monitoring processes consistent with HIPAA and HITRUST requirements.

Hands-On Technical Leadership
  • Maintain a hands-on approach to data science and AI, including the ability to write, review, and guide code in modern data science and machine learning stacks.
  • Stay close to the work by participating in model design, experimentation, and technical decision-making-especially for high-impact or clinically sensitive use cases.
  • Provide technical leadership and mentorship by reviewing approaches, validating assumptions, and ensuring analytical rigor and model quality.
  • Partner with data scientists and ML practitioners to unblock complex problems and set technical direction, without micromanaging execution.
  • Serve as a credible technical voice with Data Engineering and Application Development teams on architecture, model deployment, and MLOps practices.
  • Balance hands-on contribution with executive leadership, ensuring the organization benefits from both technical depth and strategic oversight.
  • Lead by example in adopting best practices in machine learning, responsible AI, model explainability, and production readiness in a HIPAA-regulated environment consistent with the HITRUST framework.

Cross-Functional Partnerships
  • Work closely with Data Engineering to ensure data quality, availability, and scalability.
  • Collaborate with Application Development to embed analytics and models directly into workflows and products.
  • Align on architecture, tooling, and MLOps practices that support both innovation and operational excellence.

What Success Looks Like
  • Data science solutions are embedded into daily clinical and operational workflows, not siloed.
  • Operation leaders and clinicians trust and rely on ML/AI to guide decisions.
  • Models and insights are delivered quickly, responsibly, and with clear ROI.
  • Data science is seen as a strategic partner, not a support function

Position Requirements
  • Bachelor's degree in a quantitative field (Computer Science, Statistics, Mathematics, Engineering, or similar).
  • 10+ years of experience in data science, analytics, machine learning, or applied AI, with 3+ years in senior leadership roles.
  • Proven track record of delivering data science solutions with clear business impact at scale.
  • Deep expertise in statistical modeling, machine learning, and experimental design.
  • Experience operationalizing models in production environments.
  • Demonstrated success delivering ML or advanced analytics solutions in healthcare.
  • Strong executive communication and stakeholder-management skills.

Benefits
  • Comprehensive Benefits - Medical, dental, and vision insurance, employee assistance program, employer-paid and voluntary life insurance, disability insurance, plus health and flexible spending accounts
  • Financial & Retirement Support - Competitive compensation, 401k with employer match, and financial wellness resources
  • Time Off & Leave - Paid holidays, flexible vacation time/PSSL, and paid parental leave
  • Wellness & Growth - Work life assistance resources, physical wellness perks, mental health support, employee referral program, and BenefitHub for employee discounts

About Monogram Health
Monogram Health is a leading multispecialty provider of in-home, evidence-based care for the most complex of patients who have multiple chronic conditions. Monogram Health takes a comprehensive and personalized approach to a person's health, treating not only a disease, but all of the chronic conditions that are present - such as diabetes, hypertension, chronic kidney disease, heart failure, depression, COPD, and other metabolic disorders.
Monogram Health employs a robust clinical team, leveraging specialists across multiple disciplines including nephrology, cardiology, endocrinology, pulmonology, behavioral health, and palliative care to diagnose and treat health issues; review and prescribe medication; provide guidance, education, and counselling on a patient's healthcare options; as well as assist with daily needs such as access to food, eating healthy, transportation, financial assistance, and more. Monogram Health is available 24 hours a day, 7 days a week, and on holidays, to support and treat patients in their home.
Monogram Health's personalized and innovative treatment model is proven to dramatically improve patient outcomes and quality of life while reducing medical costs across the health care continuum.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.

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