Technology

Hire a Head of Data & AI

From data chaos to decisions - and real AI outcomes

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A Head of Data & AI turns scattered data and AI ambitions into working systems and measurable results. Elevarae recruits data and AI leaders vetted by experienced technology practitioners, distinguishing genuine builders from trend-riders, across the US, Europe, India, the Philippines, and Mexico.

When Companies Come to Us

Everyone wants 'AI in the product' but nobody owns making it real

Reports disagree with each other and nobody fully trusts the numbers

Data engineering, analytics, and ML efforts are scattered across teams with no strategy

Competitors are shipping AI features while internal discussions stay theoretical

What a Great Head of Data & AI Looks Like

Has shipped data platforms and AI features that survived contact with production

Ruthlessly prioritizes business value over technical novelty

Builds the boring foundations first - quality, governance, pipelines - so the exciting work compounds

Hires well across the very different disciplines of data engineering, analytics, and ML

How Elevarae Vets Head of Data & AI Candidates

Every shortlist is built throughour structured partnership process.

Technical evaluation supported by experienced data and technology practitioners

Shipped-to-production evidence demanded for AI claims

Leadership assessment, with Predictive Index where applicable

International network for a discipline where talent is globally distributed

Data and AI leadership is where inflated résumés concentrate. Our practitioner-led vetting insists on shipped systems and measured outcomes, so the leader you hire has done the work - not just presented about it.

Frequently Asked Questions

Is this a data role or an AI role?

In most companies it must be both: AI outcomes stand on data foundations. We scope whether your first hire should lean platform (pipelines, quality, governance) or applied AI (models, features), and search accordingly.

How do you filter out AI hype from real capability?

By requiring production stories: what shipped, who used it, what it changed, what it cost. Practitioner evaluators probe those stories technically - hype rarely survives the third follow-up question.

Should this leader report to the CTO or the CEO?

Early on, usually the CTO for engineering leverage. When data becomes a company-wide operating capability, elevating the role makes sense. We'll advise based on your structure during role definition.