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Freelance Data Scientist Experimentation Jobs (NOW HIRING)

Define how data scientists contribute metrics, reports, and templates to the platform so they have high leverage when setting standards for experiments in their own space. Trust & Methodology: Verify ...

Your work will help Coframe extract reliable signals from noisy behavioral data, measure long-term ... science What you'll do: * Build experimentation frameworks that power every product line across ...

To implement quantitative and predictive models, data science experiments using literate programming techniques such as Python Jupyter Notebooks, develop appropriate visualizations of data, curate ...

About the Role We are hiring a Staff-level Data Scientist to help lead the evolution of OpenAI's core experimentation platform. This role is focused on improving the statistical rigor, reliability ...

The Data Scientist II is expected to independently lead analyses and model development projects ... Build and maintain ML/AI experiment workflows using Hex for prototyping and exploration, and AWS ...

The Data Scientist II is expected to independently lead analyses and model development projects ... Build and maintain ML/AI experiment workflows using Hex for prototyping and exploration, and AWS ...

The Data Scientist II is expected to independently lead analyses and model development projects ... Build and maintain ML/AI experiment workflows using Hex for prototyping and exploration, and AWS ...

Conduct experiments and statistical analysis to evaluate the effectiveness of business strategies. * Stay updated on industry trends and best practices regarding data science methodologies and ...

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... Conduct AI experimentation and prototyping within governed sandbox environments, including ...

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... Conduct AI experimentation and prototyping within governed sandbox environments, including ...

The Senior Data Scientist will serve as a subject matter expert and strategic partner to business ... Conduct AI experimentation and prototyping within governed sandbox environments, including ...

Data Scientist

Sunnyvale, CA ยท On-site

$110K - $190K/yr

Role Overview We are seeking a Data Scientist to work at the intersection of laboratory science and ... Working with experimental, instrument-generated, imaging, or sensor data * Exploratory data ...

Data Scientist

Pleasanton, CA ยท Remote

$75 - $80/hr

Documents and presents data science experiments and findings clearly to other data scientists and business stakeholders. * Act as peer reviewer of models and analyses built by other data scientists

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Freelance Data Scientist Experimentation information

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$37.5K

$122.7K

$196.5K

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

As of Sep 3, 2026, the average yearly pay for freelance 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 freelance data scientist experimentation do?

A Freelance Data Scientist specializing in experimentation designs, runs, and analyzes experiments (such as A/B tests) to help organizations make data-driven decisions. Their work involves formulating hypotheses, determining the right experimental design, collecting and cleaning data, and interpreting the results to provide actionable insights. Because they work on a freelance basis, they often collaborate with various companies on short-term projects or specific business challenges. Their expertise helps businesses optimize products, marketing strategies, and user experiences based on statistical evidence.

What are the key skills and qualifications needed to thrive as a freelance data scientist experimentation?

To excel as a Freelance Data Scientist Experimentation, you need expertise in statistical analysis, experimental design (such as A/B testing), and proficiency in programming languages like Python or R, often supported by a degree in a quantitative field. Familiarity with tools like SQL, data visualization platforms (e.g., Tableau), and cloud-based analytics solutions, along with certifications in data science or analytics, is highly valuable. Strong communication, problem-solving abilities, and adaptability help you interpret results and collaborate with diverse clients. These skills ensure you can independently design rigorous experiments, deliver actionable insights, and build client trust in dynamic freelance environments.

How do freelance data scientists experimentation typically collaborate with clients and stakeholders during a project?

Freelance data scientists in experimentation roles often work closely with clients to understand business objectives, design experiments, and interpret results. Collaboration usually takes place via regular check-ins, virtual meetings, and shared project management tools. Clear communication is crucial, as freelancers must articulate experimental design choices, present findings, and provide actionable recommendations to both technical and non-technical stakeholders. Establishing expectations and maintaining transparency throughout the project helps ensure successful outcomes and fosters long-term client relationships.

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

AspectFreelance Data Scientist ExperimentationFreelance Data Analyst
CredentialsTypically requires advanced degrees in data science, statistics, or related fieldsOften requires a degree in statistics, mathematics, or related fields
Work EnvironmentFocuses on designing and testing experiments, A/B testing, and model developmentInvolves data cleaning, reporting, and basic analysis of datasets
Industry UsageCommon in tech, e-commerce, and marketing for product optimizationUsed across various industries for reporting and business insights

Freelance Data Scientist Experimentation specializes in designing experiments and developing predictive models, often requiring advanced technical skills. Freelance Data Analysts focus on interpreting data, creating reports, and providing insights. While both roles analyze data, the experimentation role emphasizes testing and model validation, making it more technical and experimental in nature.

What cities are hiring for Freelance Data Scientist Experimentation jobs?

Cities with the most Freelance 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 Freelance Data Scientist Experimentation jobs?

States with the most job openings for Freelance Data Scientist Experimentation jobs include:

Senior Data Scientist - Experimental Design

Spartan Technologies, Inc.

West New York, NJ โ€ข On-site

Full-time

Re-posted 23 days ago


Job description

Senior Data Scientist - Experimental Design
We seek a Senior Data Scientist (Experimental Design) to join our client's Data Science Lab in a Hybrid role (2 days a week in Office). This is a Direct Hire opportunity.
Hybrid Office locations: New York, Holmdel, Stamford, Bethlehem, Pittsfield
Your Job
As a Senior Data Scientist, you will be responsible for developing advanced data science solutions leveraging machine learning and artificial intelligence to drive enterprise-wide innovation. You will collaborate with senior executives on high-impact, high-visibility projects to deliver AI/ML solutions and create value from our data and analytic products. Your responsibilities will include developing test and learn capabilities, designing and executing experiments, creating statistical and AI/ML models, and conducting A/B testing.
The Work
  • Develop Enterprise Test and Learn Capabilities
  • Investigating the current state of the art of experimentation practices and causal inferencing/ML techniques to identify opportunities for upscaling the methodology best practices
  • Develop and execute advanced data-driven experiments to optimize various aspects of client's business
  • Create test hypothesis, experiment design including KPI selection, and collect and analyze data
  • Develop statistical and AI/ML models to analyze experimental data and derive actionable insights
  • Apply statistical methods to assess the reliability and significance of experimental results
  • Conduct A/B testing, multivariate tests, and other experimental methodologies to optimize customer experience, product features, marketing campaigns, and other business objectives
  • Organize and manage data to extract insights that can be further incorporated into solution/model โ€ข Support use case development that includes initial data exploration, project/sample design, reception and processing of data, performing analysis and modeling to creation of final report/presentation
  • Data wrangling/data matching/ETL to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets
  • Utilize advanced statistical and AI/ML techniques to create high-performing predictive models and creative analyses to address business objectives and partner needs
  • Identify source data and data quality checks both in model/solution development and in production
  • Package model/solution and deployment in cooperation with Data Engineers and MLOps
  • Develop Deep Learning/Large Language Model/Generative AI capabilities
  • Map and mine unstructured data such as insurance contracts, medical records, sale notes, and customer servicing logs
  • AI/ML solutions include but not limited to enhancing underwriting risk assessment, claims auto adjudication, and customer servicing
  • Contribute to the overall Data Science organization
  • Collaborate with cross-functional teams of other Data Science, Data Engineering, Business groups
  • Contribute to standardization of Data Science tools, processes, and best practices

Qualifications
  • Combination of education in Statistics, Computer Science, Engineering, Applied mathematics or related field AND professional experience in Data Science or Data Analysis equaling either:
    • PhD with 2+ years professional experience
    • Master's degree with 4+ years professional experience
  • 3+ years of hands-on ML modeling/development experience
  • Strong theoretical foundations in probability & statistics, and causal inferencing techniques
  • Proven expertise in setting up hypotheses to assess consumer behavior, in designing, implementing and deploying tests
  • Strong programming skills in Python including PyTorch and/or Tensorflow
  • Solid background in algorithms and a range of ML models
  • Excellent communication skills and ability to work and collaborating cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level
  • Excellent analytical and problem-solving abilities with superb attention to detail
  • Proven leadership in providing technical leadership and mentoring to data scientists and strong management skills with ability to monitor/track performance for enterprise success

Nice to Have
  • Experience in the insurance industry
  • Experience with big data technologies such as Hadoop, Spark, and/or cloud computing
  • Knowledge of Agile development methodology
  • Experience with data visualization tools such as Tableau, QlikView, and/or D3.js

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