Head of Data Science
Heads of Data Science lead data science functions at organizations. They define strategy, build teams, and drive AI-powered insights across company.
Median Salary
$260,000
Job Growth
High — leadership critical for data organizations
Experience Level
Entry to Leadership
Salary Progression
| Experience Level | Annual Salary |
|---|---|
| Entry Level | $180,000 |
| Mid-Level (5-8 years) | $260,000 |
| Senior (8-12 years) | $340,000 |
| Leadership / Principal | $450,000+ |
What Does a Head of Data Science Do?
Heads of Data Science lead data science organizations and set technical direction. They develop data and ML strategies, build and manage high-performing data science teams, partner with business leaders to identify high-impact opportunities, establish best practices and standards, and advocate for data-driven decision-making.
A Typical Day
Strategic planning: Define data science strategy and roadmap for year
Team building: Interview and hire senior data scientists and team leads
Stakeholder meetings: Meet with executives about data strategy and opportunities
Mentoring: Coach senior data scientists and emerging leaders
Cross-functional: Identify high-impact projects across organization
Prioritization: Balance competing requests. Focus team on highest-impact work
Performance: Evaluate team. Plan growth and development for each person
Key Skills
Career Progression
Heads of Data Science typically progress to Chief Data Officer, Chief Technology Officer, or VP of Product roles.
How to Get Started
Deep DS experience: 10+ years as data scientist or ML engineer
Technical excellence: Stay technically excellent while building leadership skills
Team experience: Lead projects and small teams before leading functions
Stakeholder management: Develop ability to work with non-technical executives
Business acumen: Understand business strategy and how data science drives value
Leadership development: Pursue leadership training and coaching
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Frequently Asked Questions
What's the difference from Principal Data Scientist?▼
Principal is individual contributor. Head manages people, budgets, strategy. Different skill set required.
What does Head do?▼
Define data strategy, hire and manage data scientists, work with stakeholders, set priorities, remove blockers, grow function.
What's the hardest part?▼
Hiring great people (talent is scarce), managing expectations (not everything needs ML), stakeholder management, organizational politics.
How do you measure success?▼
Business impact from data science, team quality and retention, data culture and adoption, hiring and growth.
What preparation is needed?▼
10+ years data science experience, deep technical knowledge, team management, business acumen, strategic thinking.
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Last updated: 2026-03-07