Head of Data Science Recruiters
No postings. No stacks of resumes. No chasing. You interview a short list.
No upfront fee. You pay only if you hire.
Need someone now? Call 305-306-4829.
This is what we do all day: recruit technology and IT professionals.
A Head of Data Science must balance raw model performance against the realities of infrastructure costs and product roadmaps.
No upfront fee. You pay only if you hire.
No upfront fee. You pay only if you hire. We offer a candidate replacement guarantee on standard search agreements. The applicable period and exact terms are set out in the signed client recruiting agreement.
What happens next
- Do I pay upfront?
- No upfront fee. You pay only if you hire.
- Must I give you exclusivity?
- We do not promise or require exclusivity here. Any terms are in the recruiting agreement we refer you to.
- Will you reveal my company?
- Not without your explicit consent before we disclose anything.
- What if I do not hire?
- No hire, no fee.
- No upfront fee
- Pay only if you hire
- Technology only
- We reach engineers who aren't on job boards
- Replacement guarantee on standard searches
Need someone now? Call 305-306-4829.
What this hire really comes down to
A Head of Data Science must balance raw model performance against the realities of infrastructure costs and product roadmaps. This is not a research position. You need an individual who understands how to prioritize model development based on potential return rather than purely mathematical novelty. The core challenge lies in preventing teams from becoming trapped in endless prototyping loops that fail to produce deployable assets. You need a leader who defines success by the integration of data science into your operational workflows.
The right hire must translate complex analytical findings for executive stakeholders who do not speak code. They should possess the authority to kill unproductive projects early and the technical depth to mentor senior analysts through complex architectural decisions. Look for someone who views data as a product that requires version control, monitoring, and maintenance. They must establish the technical culture that values reproducible results over academic precision while keeping the team aligned with your internal revenue targets.
What we check before you see anyone
Production System Design
Ask them to explain how they moved a model from a notebook environment to a live production state. Look for awareness of containerization, API latency requirements, and model drift detection. Weak candidates focus on accuracy metrics alone, ignoring the engineering overhead of deployment.
Business Impact Quantification
Press them for a narrative regarding a specific model they built that changed a business decision. They should be able to articulate the before and after state in terms of efficiency, cost reduction, or revenue growth rather than just talking about F1 scores or hyperparameter tuning.
Prioritization Frameworks
Verify how they manage a backlog when multiple departments request competing projects. A competent head will use a clear rubric based on expected value, effort, and risk to justify their choices to stakeholders. Beware of those who simply prioritize based on whoever has the loudest voice in the boardroom.
Technical Mentorship
Discuss a time they corrected a subordinate’s technical approach. A strong leader provides specific guidance on methodology, such as choosing a simpler linear model over a complex neural network when data density is low. They must show they prioritize team learning over their own output.
Where we find them
Search for individuals currently leading teams at companies that prioritize high-volume data processing rather than those operating in pure research environments. Look for patterns of long-term retention within the same technical group, which suggests an ability to build and maintain systems over several years rather than just building and leaving.
Motivation should center on scaling teams and infrastructure. Seek candidates who moved from individual contributor roles into management and express frustration with poorly scoped projects or disjointed technical stacks. They should be seeking a role that offers autonomy to define the data infrastructure strategy rather than just reacting to ad-hoc requests from other internal department heads.
Mistakes we see
Prioritizing hiring a master of a single niche algorithm over someone who can build a functional, reliable data pipeline from end to end.
Ignoring the candidate's inability to manage cloud infrastructure costs, leading to ballooning AWS or GCP spend that ruins project margins.
Selecting a candidate who lacks the political nuance required to say no to executives when requested models have no clear path to producing actual data-driven decisions.
The search in three steps
Agree the brief
During intake, define the specific operational constraints of your environment, such as legacy data silos or strict latency requirements, to see if the candidate has practical experience overcoming these common blockers.
Find and speak with people
In the headhunt phase, review the candidate's history for evidence of team expansion. Did they successfully mentor junior staff into senior roles, or did the team remain stagnant during their tenure?
Introduce the people who fit
For the final evaluation, conduct a deep dive into a past failure. A strong candidate will openly discuss what they learned about model limitations, infrastructure gaps, or communication breakdowns without blaming their previous peers or management.
Questions about this search
How should I structure the compensation for this leadership role?
Base salaries are standard for this level, but ensure your equity package reflects their role in mitigating long-term technical debt. Avoid purely performance-based bonuses tied to model accuracy, as this incentivizes overfitting rather than reliable business utility.
What if my top candidate receives a counteroffer from their current firm?
If they consider a counteroffer, it usually indicates their core motivation is salary rather than technical ownership. Let them walk, as you need a leader who is committed to building your specific vision rather than someone looking for a raise.
Is remote work feasible for a Head of Data Science?
Remote work is entirely viable provided they can demonstrate a history of managing distributed teams using clear documentation. Ensure your interview process tests their ability to communicate technical requirements asynchronously to avoid local communication silos.
How do I ensure a candidate is a technical fit for my stack?
Focus on their ability to learn your specific tools rather than matching their exact tech stack experience. Someone who has led teams in a major cloud environment will pick up your specific tools quickly if they understand the underlying architectural patterns.
What are the common constraints on my candidate shortlist?
The primary constraint is finding someone who balances engineering rigor with commercial awareness. Most candidates are either excellent engineers who lack leadership skills or managers who have lost touch with modern machine learning development patterns.
No upfront fee. You pay only if you hire. We offer a candidate replacement guarantee on standard search agreements. The applicable period and exact terms are set out in the signed client recruiting agreement.
What happens next
- Do I pay upfront?
- No upfront fee. You pay only if you hire.
- Must I give you exclusivity?
- We do not promise or require exclusivity here. Any terms are in the recruiting agreement we refer you to.
- Will you reveal my company?
- Not without your explicit consent before we disclose anything.
- What if I do not hire?
- No hire, no fee.
Pay snapshot
Head of Data Science
$175,140
Median as published, released May 15, 2026. Matched to Computer and Information Systems Managers (SOC 11-3021).
BLS reports Computer and Information Systems Managers as a broader occupation. It does not separate Head of Data Science, technology stack, seniority, certifications or employer sector. These figures are not a title-specific offer range.
Source: BLS OEWS May 2025.
See the salary guideHow a search runs
The Six-Step Search
- 1Search Calibration
A call about the work. You get a written search profile.
- 2Market Mapping
We identify the employer backgrounds that fit. You see where we will look.
- 3Professional Contact Intelligence
We identify individual people, not job board applicants.
- 4Persistent Personalized Outreach
Personal outreach and direct follow-through. You get search updates.
- 5Live Candidate Qualification
A recruiter checks stack, scope and motivation in conversation.
- 6Candidate Intelligence and Process Support
You receive a written brief on every person you meet.
Working with Technology Headhunters
When is the recruiting fee due?
There is no upfront fee for our contingency search. You pay only if you hire someone we present, under the terms of the signed agreement.
What are the replacement terms?
We offer a candidate replacement guarantee on standard search agreements. The applicable period and exact terms are set out in the signed client recruiting agreement.
What don't you do in a permanent search?
We do not bill by the hour for permanent search or charge a retainer unless one is agreed. We do not treat reposting your job advertisement as headhunting.