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Head Data Scientist Jobs (NOW HIRING)

HEB

Data Scientist - ML Engineering

San Antonio, TX · On-site

$158K/yr

HEAD FOR BUSINESS... skills to serve as technical lead to support decision-making for complex cross ... with data scientists, data engineers, and stakeholders to understand and fulfill their ...

Independence Pet Group

Lead Data Scientist

Chicago, IL · On-site

Reporting to the Head of Analytics, the Lead Data Scientist will help shape the data science roadmap, champion best practices in experimentation and modeling, and contribute to building a strong ...

HG Insights

Applied Data Scientist - Research

Role Overview The Applied Data Scientist - Research is a collaborative analytical partner to the Head of Data Science, contributing to the design and validation of GTM insights that power the ...

New

Rockstar

Senior Data Scientist

$115K - $140K/yr

Your Role They are seeking a Data Scientist to join the team. Do you love working in machine ... If you learn continuously, tackle challenges head-on, and know your strengths and gaps intimately ...

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Head Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do head data scientist jobs pay per year?

As of Jun 12, 2026, the average yearly pay for head data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

How does a Head Data Scientist typically balance hands-on technical work with leadership responsibilities?

As a Head Data Scientist, you'll often split your time between high-level strategy, team leadership, and advanced technical problem-solving. While you'll guide project direction, mentor junior scientists, and collaborate with stakeholders, you'll also be expected to stay engaged with the latest analytical techniques and occasionally contribute directly to model development or code reviews. Striking this balance requires excellent time management and the ability to delegate effectively while ensuring technical standards remain high. Regular communication with both your team and other departments is essential to align data initiatives with business goals.

What is the difference between Head Data Scientist vs Data Scientist?

AspectHead Data ScientistData Scientist
CredentialsMaster's or PhD in Data Science, Statistics, or related fieldsBachelor's or Master's in relevant fields
Work EnvironmentLeads teams, strategic planning, oversees projectsExecutes data analysis, builds models, reports findings
Industry UsageCommonly found in organizations with large data teamsWidespread across industries for data analysis roles

The Head Data Scientist focuses on leadership, strategy, and overseeing data initiatives, while the Data Scientist primarily handles hands-on data analysis and modeling. Both roles require strong technical skills, but the Head Data Scientist has additional responsibilities in team management and strategic planning.

What are Head Data Scientists?

Head Data Scientists are senior professionals who lead data science teams in analyzing large datasets to extract insights, drive decision-making, and solve complex business problems. They set the strategic direction for data science initiatives, collaborate with other departments, and ensure that data-driven solutions align with organizational goals. In addition to overseeing technical work, they also mentor team members, manage projects, and often communicate findings to executive leadership.

What are the key skills and qualifications needed to thrive as a Head Data Scientist, and why are they important?

A Head Data Scientist needs deep expertise in statistics, machine learning, and data analytics, typically supported by an advanced degree in a quantitative field. Proficiency with programming languages such as Python or R, cloud platforms, big data tools, and experience leading data science projects are crucial. Strong leadership, strategic thinking, and communication skills help guide teams and align data initiatives with business goals. These competencies ensure effective team management, innovative solutions, and measurable business impact from data-driven strategies.
More about Head Data Scientist jobs
What cities are hiring for Head Data Scientist jobs? Cities with the most Head Data Scientist job openings:
What are the most commonly searched types of Data Scientist jobs? The most popular types of Data Scientist jobs are:
What states have the most Head Data Scientist jobs? States with the most job openings for Head Data Scientist jobs include:
What job categories do people searching Head Data Scientist jobs look for? The top searched job categories for Head Data Scientist jobs are:
Head Data Scientist jobs near you
Infographic showing various Head Data Scientist job openings in the United States as of June 2026, with employment types broken down into 84% Full Time, 4% Part Time, 4% Temporary, 4% Contract, and 4% Nights. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Senior Marketing Data Scientist

Senior Marketing Data Scientist

Kikoff

San Francisco, CA • On-site

Other

Posted 22 days ago

Job description

The Role

You'll be the analytical engine behind Kikoff's paid media channels - owning diagnostics, experimentation, and measurement that inform tens of millions in spend decisions. This is not a reporting role. You'll work at the intersection of causal inference, channel economics, and attribution, partnering closely with Growth leadership and our Head of Marketing Data Science.

Responsibilities

  • Own marketing measurement and attribution frameworks across paid channels (e.g., Google, Meta, TikTok, TV), including experimentation, incrementality testing, and attribution modeling to quantify channel effectiveness and guide budget allocation
  • Build and operationalize scalable measurement solutions such as Marketing Mix Models (MMM), channel-level performance diagnostics, and CAC/LTV forecasting to support growth decisions and optimize marketing spend
  • Design and execute 5-6 incrementality tests annually, including power analysis, monitoring, and executive readouts
  • Reconcile platform-reported metrics with internal attribution models and MMM (Northbeam) outputs
  • Build and maintain real-time anomaly detection across acquisition channels
  • Support brand test design and translate NPS/sentiment signals into growth insights

Qualifications

  • 4+ years in data science or analytics, with at least 2 years in marketing or growth contexts
  • Expert SQL and strong Python; deep familiarity with experimentation design and causal inference methods
  • Experience with paid media channels and platform-level attribution mechanics
  • Comfort with MMM outputs and reconciling econometric findings with channel data
  • Strong communicator - able to translate statistical results into clear recommendations for non-technical stakeholders
  • Bachelor's or advanced degree in a quantitative discipline

Bonus Points

  • Hands-on experience with incrementality frameworks (geo-based, time-based, ghost ads)
  • Familiarity with Northbeam, Rockerbox, or similar attribution tooling
  • Background in fintech, consumer lending, or subscription growth

Apply