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Senior 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 ...

PlayStation Global

OR · On-site

Staff Data Scientist - Experimentation & Measurement Overview: As a Staff Data Scientist on the ... senior leadership. * Mentor and guide other Data Scientists, providing thought leadership and ...

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.

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$142.5K

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

As of Aug 12, 2026, the average yearly pay for senior data scientist experimentation in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

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

AspectSenior Data Scientist ExperimentationData Scientist Experimentation
Required CredentialsMaster's or PhD in Data Science, Statistics, or related field; extensive experienceBachelor's or Master's in relevant field; less experience required
Work EnvironmentLeads experimentation projects, mentors junior staff, influences strategyExecutes experiments, analyzes data, supports decision-making
Employer & Industry UsageTech companies, e-commerce, finance; roles in innovation teamsStartups, tech firms, research teams; common in data-driven industries

Senior Data Scientist Experimentation typically involves leading complex experimentation projects, mentoring team members, and shaping strategic decisions. Data Scientist Experimentation focuses on executing experiments, analyzing results, and supporting data-driven decisions. The senior role requires more experience, leadership, and strategic influence within organizations.

What does a senior data scientist experimentation do?

A Senior Data Scientist Experimentation designs and analyzes experiments, such as A/B tests, to help organizations make data-driven decisions. They develop methodologies to test hypotheses, interpret results, and provide actionable insights to improve products or services. In addition to technical expertise in statistics and data analysis, they often collaborate with product managers, engineers, and other stakeholders to ensure experiments are well-structured and aligned with business goals. Their work helps organizations optimize features, understand user behavior, and drive innovation.

How does a senior data scientist experimentation typically interact with cross-functional teams during the design and analysis of experiments?

Senior Data Scientists focused on experimentation collaborate closely with product managers, engineers, designers, and business stakeholders to define experiment goals and ensure alignment with product strategy. They guide teams in establishing proper experimental design, such as randomized controlled trials or A/B tests, and are responsible for communicating methodology and results in an accessible way. Regular cross-functional meetings and iterative feedback loops are common, allowing for agile adjustments and shared understanding of experimental outcomes, which ultimately drive data-informed decision making across the organization.

What are the key skills and qualifications needed to thrive as a senior data scientist experimentation, and why are they important?

To excel as a Senior Data Scientist Experimentation, you need deep expertise in statistical analysis, experimental design (such as A/B testing), and a strong background in data science or a related quantitative field. Proficiency with tools like Python, R, SQL, and experimentation platforms, as well as familiarity with cloud services and version control, is typically required. Outstanding problem-solving, communication, and stakeholder management skills are crucial for translating complex findings into actionable business insights. These abilities ensure robust experimentation, accurate data-driven decisions, and effective collaboration across teams.
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Senior Data Scientist Experimentation jobs near you
Infographic showing various Senior 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 $142,460 per year, or $68.5 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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