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Evening 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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Evening Data Scientist Experimentation information

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

As of Jul 31, 2026, the average yearly pay for evening 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 the difference between Evening Data Scientist Experimentation vs Data Scientist?

AspectEvening Data Scientist ExperimentationData Scientist
Work HoursPrimarily evening shifts, flexible schedulingTypically standard daytime hours
FocusExperimentation, testing new models during off-hoursBroader data analysis, modeling, and reporting
CredentialsSame as Data Scientist (degree, skills)Degree in data science, statistics, or related field
Work EnvironmentData teams, labs, or remoteOffice or remote, collaborative teams

Evening Data Scientist Experimentation focuses on conducting experiments and testing models during evening hours, often to optimize workflows or handle specific projects. In contrast, Data Scientists typically work during standard hours on a wide range of data analysis tasks. Both roles require similar credentials but differ mainly in scheduling and specific focus areas.

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Evening Data Scientist Experimentation jobs near you

Data Scientist & Experimentation Analyst

MDAEdge

Remote

Full-time

Re-posted 3 days ago

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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