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Experimental Design Jobs (NOW HIRING)

Pacific Fusion

Mechanical Design Engineer

San Leandro, CA

$85K - $116K/yr

Lead experimental design and testing in collaboration with internal teams, external vendors, and academic partners * Conduct research into novel sealing techniques; define, execute, and evaluate test ...

Ametek

Mechanical Design & Validation Engineer

Wilmington, MA · On-site

$83K - $112K/yr

This role combines mechanical design with hands-on experimentation, prototype development, and environmental validation, ensuring products perform reliably under extreme conditions. The engineer will ...

Pacific Fusion

Mechanical Design Engineer

Fremont, CA

$83K - $112K/yr

Lead experimental design and testing in collaboration with internal teams, external vendors, and academic partners * Conduct research into novel sealing techniques; define, execute, and evaluate test ...

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How much do experimental design jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for experimental design in the United States is $26.25, according to ZipRecruiter salary data. Most workers in this role earn between $20.19 and $30.05 per hour, depending on experience, location, and employer.

What is an experimental design?

An Experimental Design job involves planning, structuring, and analyzing experiments to ensure reliable and valid results. Professionals in this role use statistical methods to test hypotheses, optimize processes, and improve decision-making in fields such as science, engineering, and business. They design experiments to minimize bias, control variables, and maximize the accuracy of conclusions. This role is crucial in research and development, product testing, and process optimization across various industries.

What are some common challenges faced by professionals in experimental design roles?

One common challenge in Experimental Design roles is ensuring that experiments are both scientifically rigorous and feasible given constraints like budget, time, or available resources. Additionally, dealing with unexpected variables or data inconsistencies can require creative problem-solving and the ability to adapt research protocols. Team collaboration is also key, as experimental designers often work closely with scientists, engineers, and statisticians to develop and refine testing procedures. By anticipating potential obstacles and communicating clearly with stakeholders, professionals in this role contribute to successful and reliable research outcomes.

What are the key skills and qualifications needed to thrive in the experimental design position, and why are they important?

To excel in Experimental Design, a professional needs a strong background in statistics, scientific methodology, and data analysis, typically supported by an advanced degree in a related field. Familiarity with statistical software (such as R, SPSS, or SAS), laboratory equipment, and protocol management systems is often required. Strong attention to detail, critical thinking, and effective communication are crucial soft skills in this position. These capabilities are vital for ensuring research integrity, reproducibility, and clear reporting of experimental outcomes.

What do you do in experimental design?

In experimental design, a professional plans and structures experiments to test hypotheses, ensuring variables are controlled and data collection methods are appropriate. This involves selecting suitable sample sizes, randomization, and statistical analysis to produce valid and reliable results.
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Experimental Design jobs near you
Infographic showing various Experimental Design job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $54,595 per year, or $26.2 per hour.

Senior Data Scientist - Experimental Design

Spartan Technologies, Inc.

West New York, NJ • On-site

Full-time

Re-posted 22 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 • 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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