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Trainee 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

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 trainee data scientist experimentation jobs pay per year?

As of Jul 29, 2026, the average yearly pay for trainee 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 does a Trainee Data Scientist Experimentation do?

A Trainee Data Scientist Experimentation assists in designing, conducting, and analyzing experiments to solve business problems using data. They work closely with senior data scientists to learn methods such as A/B testing, statistical analysis, and machine learning. Their responsibilities often include preparing datasets, running analyses, and interpreting results to provide actionable insights. This role provides hands-on experience in using data science tools and techniques in a real-world environment while developing skills necessary for more advanced data science positions.

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

To thrive as a Trainee Data Scientist Experimentation, you generally need a solid background in statistics, data analysis, and experimental design, often supported by a degree in a quantitative field such as mathematics, computer science, or engineering. Familiarity with programming languages like Python or R, experience with data visualization tools, and knowledge of A/B testing platforms are typically required. Strong problem-solving skills, curiosity, and effective communication set candidates apart in this role. These skills are crucial for designing robust experiments, interpreting complex data, and communicating insights that drive data-informed decision-making.

What is the difference between Trainee Data Scientist Experimentation vs Data Analyst?

AspectTrainee Data Scientist ExperimentationData Analyst
Required CredentialsTypically a degree in data science, statistics, or related field; some programming knowledgeOften a degree in statistics, mathematics, or related field; proficiency in Excel and SQL
Work EnvironmentCollaborative teams focusing on experimental design, A/B testing, and data modelingAnalyzing data sets, creating reports, and visualizations for business insights
Employer & Industry UsageStartups, tech companies, and research labs experimenting with data-driven solutionsCorporate businesses across finance, marketing, and retail sectors

While both roles involve working with data, Trainee Data Scientist Experimentation focuses on designing and testing experiments to derive insights, often requiring programming and statistical skills. Data Analysts primarily interpret existing data to generate reports and support decision-making. The roles overlap in data handling but differ in scope and technical depth.

What types of projects and collaborative opportunities can a Trainee Data Scientist in experimentation expect during the early stages of their career?

As a Trainee Data Scientist specializing in experimentation, you will typically work on projects involving A/B testing, statistical analysis, and data-driven decision-making to optimize products or processes. You'll often collaborate closely with product managers, engineers, and senior data scientists to design experiments and interpret results. Early in your role, you'll likely contribute to setting up test frameworks, analyzing user behavior data, and presenting findings to cross-functional teams. This environment not only builds your technical and analytical skills but also enhances your ability to communicate insights and work collaboratively across departments.
What cities are hiring for Trainee Data Scientist Experimentation jobs? Cities with the most Trainee 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 Trainee Data Scientist Experimentation jobs? States with the most job openings for Trainee Data Scientist Experimentation jobs include:
Trainee Data Scientist Experimentation jobs near you

Data Scientist & Experimentation Analyst

MDAEdge

Remote

Full-time

Re-posted yesterday

Job description

Job Summary:
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 insights and rigorous experimentation to enable end-to-end support for machine learning initiatives.
Responsibilities:
• Design, execute, and interpret controlled experiments (e.g., A/B tests, multivariate tests) to evaluate the effectiveness of ML models and strategies.
• Conduct exploratory data analysis (EDA), hypothesis testing, and statistical modelling to support ML and business objectives.
• Assist ML Scientists in preparing data, engineering features, and evaluating models for pricing and personalization solutions.
• Create dashboards and visualizations to track key metrics, experiment outcomes, and model performance.
• Perform deep dives and provide actionable insights on specific datasets or business questions to inform strategic decisions.
• Partner with ML Scientists, Data Engineers, and Product Managers to align on experimentation goals and ensure successful implementation of ML solutions.
Qualifications:
Required:
• 4+ years in data science, experimentation analysis, or a related role supporting ML projects and experimentation.
• Strong understanding of statistical methods, experiment design, and causal inference techniques.
• Proficiency in Python for data manipulation & machine learning (Pandas, NumPy, sci-kit-learn).
• Intermediate skills in SQL for data querying, including Window Functions, Joins, and Group By.
• Familiarity with classical ML techniques like Classification, Regression, and Clustering, using algorithms like XGBoost, Random Forest, and KMeans.
• Experience with data visualization platforms (e.g., Tableau, Power BI, Matplotlib, or Seaborn).
• Proficiency in designing and analyzing A/B and multivariate experiments, focusing on drawing actionable insights.
• Experience working with large, complex datasets, including preprocessing, feature engineering, and encoding techniques.
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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