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Executive Data Scientist Experimentation Jobs (NOW HIRING)

MDAEdge

Data Scientist & Experimentation Analyst

MDAEdge is seeking a Data Scientist & Experimentation Analyst to support the development and evaluation of ML-driven pricing and personalization solutions. This role involves providing data-driven ...

FanDuel

Data Scientist, Experimentation

New York, NY · On-site

The Data Scientist will partner with retention marketing stakeholders and will be responsible for designing and analyzing experiments that help to answer key questions and drive promotional strategy.

FanDuel

Data Scientist, Experimentation

Manhattan, NY · On-site

The Data Scientist will partner with retention marketing stakeholders and will be responsible for designing and analyzing experiments that help to answer key questions and drive promotional strategy.

PlayStation Global

OR · On-site

Staff Data Scientist - Experimentation & Measurement Overview: As a Staff Data Scientist on the Decision Science team at PlayStation, you will take a leading role in designing and interpreting ...

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How much do executive data scientist experimentation jobs pay per year?

As of Aug 12, 2026, the average yearly pay for executive data scientist experimentation 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.

What is an executive data scientist experimentation?

An Executive Data Scientist Experimentation is a senior-level professional who leads and oversees the design, implementation, and analysis of experiments and data-driven initiatives within an organization. They are responsible for developing experimentation strategies, guiding teams in A/B testing, and ensuring that data insights drive business decisions. This role often collaborates with executive leadership to align data science projects with strategic goals and maximize business impact. Executive Data Scientists also mentor junior staff, set best practices, and ensure that experimentation methods are rigorous and ethical.

What is the difference between Executive Data Scientist Experimentation vs Data Scientist Experimentation?

AspectExecutive Data Scientist ExperimentationData Scientist Experimentation
CredentialsAdvanced degrees (Master's/PhD), leadership experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentStrategic planning, cross-department collaboration, leadership rolesData analysis, model development, experimentation execution
Employer & Industry UsageTech companies, finance, consulting firms with strategic focusTech, e-commerce, healthcare, and other data-driven industries

Executive Data Scientist Experimentation roles focus on strategic oversight, leadership, and aligning experimentation efforts with business goals. Data Scientist Experimentation roles are more hands-on, involving designing and executing experiments to analyze data and inform decisions. Both roles require strong analytical skills, but the executive level emphasizes leadership and strategic impact.

How does an executive data scientist experimentation typically collaborate with cross-functional teams to drive business impact?

As an Executive Data Scientist focusing on experimentation, you will frequently partner with product managers, engineers, and business leaders to design and interpret experiments that inform strategic decisions. Your role involves translating business questions into measurable hypotheses, guiding teams on best practices for A/B testing, and ensuring rigorous analysis. Effective communication is key, as you'll need to present complex findings in a clear way that supports decision-making across the organization. This collaborative approach not only maximizes the impact of your data insights but also fosters a culture of evidence-based innovation.

What are the key skills and qualifications needed to thrive as an executive data scientist experimentation?

To thrive as an Executive Data Scientist Experimentation, you need advanced expertise in statistics, experimental design, and data modeling, typically backed by a PhD or master's degree in a quantitative field. Mastery of tools such as Python, R, SQL, and platforms like AWS or Azure, along with experience in A/B testing and big data systems, is essential. Leadership, strategic thinking, and strong communication skills are crucial for guiding teams and translating complex data into actionable business insights. These skills and qualities are vital for driving data-driven decision-making and delivering impactful business results through rigorous experimentation.
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Executive Data Scientist Experimentation jobs near you
Infographic showing various Executive Data Scientist Experimentation job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Cupertino, United States On-site Apple Senior Data Scientist, Experimentation & Causal Inference

Experimentation Jobs

Cupertino, CA • On-site

$120 - $150/hr

Other

Posted 7 days ago

Job description

Why Here?

Apple is seeking a Senior Data Scientist, Experimentation & Causal Inference to help advance the scientific foundations of measurement, experimentation, and organizational learning across Apple Services. The role sits at the intersection of statistics, causal inference, experimental design, and decision-making. This position plays a pivotal role in establishing experimentation standards, developing advanced causal methodologies, building experimentation intelligence systems, and driving cross-experiment learning initiatives.

What Will You Do?

As a Senior Data Scientist, Experimentation & Causal Inference at Apple, you will own key components of the experimentation science ecosystem and work across product, growth, engineering, data engineering, and strategic science teams to define measurement frameworks. You will establish experimentation standards, develop advanced causal methodologies, and build experimentation intelligence systems for cross-experiment learning initiatives. Additionally, you will help evolve experimentation methodologies to evaluate increasingly complex product behaviors and long-term user outcomes.

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