Chief Data Officer

Heads up: this posting is for future opportunities rather than one specific open role. If you apply, we’ll add you to our candidate network and may reach out when relevant roles come up.

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What the market looks like

We've tracked 600+ senior-level data science postings across the US over the last six months, with concentrated hiring in California, New York, and Washington. Chief Data Officer roles span technology, financial services, healthcare, and professional services — sectors where data-driven decision-making directly impacts competitive advantage. The median compensation for executive-level data science leaders lands around $240,000 base, with top-of-market packages reaching $470,000. The strongest candidates bring a mix of technical depth in analytics and ML infrastructure, proven ability to scale data teams and platforms, and credibility translating complex data work into business outcomes for C-suite stakeholders.

Job responsibilities

• Own the data strategy and roadmap — define how data science, analytics, and ML capabilities drive business value and competitive differentiation across the organization

• Build and scale the data science and analytics organization — hire, mentor, and retain talent; establish team structure, culture, and processes that ship reliable insights and models

• Partner with C-suite and business leaders to translate data-driven findings into strategic decisions and operational improvements

• Lead architecture and governance decisions for data infrastructure, pipelines, and ML systems — ensuring quality, security, and scalability as the organization grows

• Drive adoption of data culture across the company — establish frameworks for experimentation, measurement, and iteration

• Manage the data science budget and ROI; prioritize initiatives based on business impact and resource constraints

• Represent data science leadership in board-level or investor conversations, communicating technical progress and business implications

Candidate requirements

• 8+ years building and leading data science, analytics, or ML organizations — with at least 3 years in a director-level or C-suite role

• Hands-on technical fluency in data science, statistical modeling, and ML — you understand the work deeply even as you move away from day-to-day coding

• Proven track record scaling data teams from scratch and/or transforming a data function — establishing processes, governance, and culture that stick

• Experience translating technical work into business language; ability to present data insights and roadmaps confidently to non-technical executives and boards

• Strong financial acumen — you can articulate data science ROI, manage budgets, and make trade-offs between exploration and production-grade work