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Junior 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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Junior Data Scientist Experimentation information

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

As of Aug 7, 2026, the average yearly pay for junior 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 types of projects and responsibilities can a junior data scientist experimentation expect to handle during their first year?

As a Junior Data Scientist Experimentation, you can expect to work on A/B testing, designing experiments to evaluate new product features, and analyzing data to provide actionable insights. Typically, you'll collaborate closely with product managers, engineers, and senior data scientists to set up experiments and interpret results. You'll also be responsible for cleaning data, running statistical analyses, and helping to communicate your findings to non-technical stakeholders. Over time, you'll gain exposure to more complex experimental designs and have opportunities to contribute to larger-scale projects as you build your skills.

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

AspectJunior Data Scientist ExperimentationJunior Data Scientist
Required CredentialsBachelor's in Data Science, Statistics, or related field; some certifications in experimentation or A/B testingBachelor's in Data Science, Statistics, or related field; basic knowledge of data analysis
Work EnvironmentFocus on designing and analyzing experiments, A/B testing, and optimizing processesData analysis, reporting, and building models across various projects
Employer & Industry UsageTech companies, e-commerce, marketing agenciesFinance, healthcare, tech, and consulting firms

Junior Data Scientist Experimentation specializes in designing and analyzing experiments to optimize products and processes, while Junior Data Scientist has a broader role in data analysis and modeling. Both roles require similar educational backgrounds but differ in focus and daily tasks.

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

To thrive as a Junior Data Scientist Experimentation, you need a solid background in statistics, experimental design, and programming (commonly with Python or R), typically supported by a relevant degree in data science, statistics, or a related field. Familiarity with A/B testing platforms, SQL databases, and data visualization tools like Tableau or Power BI is essential. Strong analytical thinking, curiosity, and effective communication skills help you interpret results and share findings with cross-functional teams. These competencies ensure accurate experimental analyses, actionable insights, and impactful contributions to data-driven decision-making.

What does a junior data scientist experimentation do?

A Junior Data Scientist Experimentation is responsible for helping design, run, and analyze experiments—such as A/B tests—to guide data-driven decisions within an organization. They assist in collecting and cleaning data, applying statistical techniques, and interpreting the results to provide actionable insights. This role typically works closely with senior data scientists and business teams to ensure experiments are methodologically sound and findings are communicated clearly. The position is ideal for those with foundational knowledge in statistics, programming, and data analysis who are looking to build practical experience.
What cities are hiring for Junior Data Scientist Experimentation jobs? Cities with the most Junior Data Scientist Experimentation job openings:
What are the most commonly searched types of Data Scientist Experimentation jobs? The most popular types of Data Scientist Experimentation jobs are:
What states have the most Junior Data Scientist Experimentation jobs? States with the most job openings for Junior Data Scientist Experimentation jobs include:
Junior Data Scientist Experimentation jobs near you

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

Experimentation Jobs

Cupertino, CA • On-site

$120 - $150/hr

Other

Posted 2 days ago

New

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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