Head of Business Analytics

Career Guide

Heads of Business Analytics set the vision and lead teams that turn data into decisions. They define KPIs, build dashboards and experiments, and partner with executives to drive growth, efficiency, and risk management across the company.

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Key Responsibilities

Set analytics strategy aligned to business goals
Build and manage analytics, BI, and data science teams
Define KPI frameworks and performance measurement
Oversee data governance, quality, and access policies
Lead experimentation (A/B testing) and causal analysis
Translate executive questions into analytics roadmaps
Deliver insights and recommendations that drive decisions

Career Progression

Can Lead To

VP of Analytics

Chief Data Officer (CDO)

Head of Data Science

Transition Opportunities

Data Product Manager

Strategy & Operations Leader

Management Consultant (Analytics)

Revenue Operations Leader

Common Skill Gaps

Often Missing Skills

Enterprise data architecture and governanceExperimental design and causal inference at scaleKPI frameworks linking metrics to P&L outcomesLeading and scaling multi-disciplinary analytics teams

Development SuggestionsLead a company-wide KPI/measurement initiative and own data governance; complete CAP or an A/B testing specialization to formalize methods.

Market Intelligence Report

Head of Business Analytics is part of the Business Intelligence category.Explore our market intelligence report to see how AI and hiring demand are shifting for these roles.

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Salary & Demand

Median Salary Range

Entry LevelUS$140,000–$170,000

Mid LevelUS$170,000–$210,000

Senior LevelUS$210,000–$280,000

Growth Trend

growing - Broad adoption of data/AI boosts demand for analytics leadership

Companies Hiring

Major Employers

AmazonJPMorgan Chase & Co.UnitedHealth Group

Industry Sectors

TechnologyFinancial ServicesHealthcareRetail & E-commerceConsulting

Recommended Next Steps

Earn CAP and a BI certification (Tableau or Power BI); build an executive portfolio with KPI playbooks and dashboards.

Lead a cross-functional experimentation program; publish results tying metrics to revenue/cost impacts.

Join data leadership communities and present at meetups; conduct informational interviews with analytics executives.