ZipRecruiter

Log In

1

Experimental Design Jobs (NOW HIRING)

Owens Corning

Program Leader

Granville, OH · On-site

PURPOSE OF THE JOB The Experimental Design and Product Testing Leader provides strategic technical and people leadership for the Experimental Design and Product Testing team within Insulation R&D.

Owens Corning

Program Leader

Granville, OH

PURPOSE OF THE JOB The Experimental Design and Product Testing Leader provides strategic technical and people leadership for the Experimental Design and Product Testing team within Insulation R&D.

Archer Daniels Midland

Independently design, execute, and lead pilot-scale extrusion trials and experiments * Manage R&D projects from concept through commercialization, ensuring timelines and technical deliverables are ...

New

MIT Human Resources

Project Engineer

Cambridge, MA

PROJECT ENGINEER , The Nuclear Reactor Laboratory , will be responsible for a wide range of experimental design, operation, and data-taking activities supporting the primary research mission of the ...

next page

Showing results 1-20

All JobsExperimental Design Jobs

Experimental Design information

See salary details

$14

$26

$43

How much do experimental design jobs pay per hour?

As of Jun 26, 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 job?

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 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 are some high paying design jobs?

High paying design jobs include roles such as user experience (UX) designer, industrial designer, and creative director, often requiring advanced skills and experience. These positions typically offer higher salaries due to their complexity, leadership responsibilities, and demand for specialized expertise, with salaries varying by industry and location.

What careers can DT lead to?

Experimental design careers can lead to roles such as research scientist, data analyst, product developer, or clinical trial coordinator. These positions often require strong analytical skills, knowledge of research methods, and proficiency with statistical tools or software. Advancement may involve specialization in a specific field or obtaining relevant certifications.

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 is an experimental designer?

An experimental designer is a professional who plans and develops experiments to test hypotheses and gather data, often in scientific or research settings. They use principles of scientific methodology, statistical analysis, and design tools to ensure valid and reliable results.

What are examples of experimental design?

Experimental design in research involves planning how to conduct experiments to test hypotheses, often using methods such as randomized controlled trials, factorial designs, or crossover studies. In an experimental design role, understanding how to control variables, select appropriate samples, and analyze data with statistical tools is essential for ensuring valid and reliable results.
More about Experimental Design jobs
What cities are hiring for Experimental Design jobs? Cities with the most Experimental Design job openings:
What states have the most Experimental Design jobs? States with the most job openings for Experimental Design jobs include:
What job categories do people searching Experimental Design jobs look for? The top searched job categories for Experimental Design jobs are:
Experimental Design jobs near you
Infographic showing various Experimental Design job openings in the United States as of June 2026, with employment types broken down into 14% Full Time, 65% Part Time, and 21% Contract. Highlights an 73% Physical, 1% Hybrid, and 26% Remote job distribution, with an average salary of $54,595 per year, or $26.2 per hour.

Digital Innovation Engineer

Celanese International Corporation

Wilmington, DE • Hybrid

Full-time

Posted 6 days ago

Job description

Celanese Engineered Materials is seeking an Engineer, Digital Innovation – Predictive Modeling & Advanced Experimentation role. This role is a specialized technical position focused on applying AI + Physics into predictive modeling, experimental design, and Bayesian optimization to enable faster, more confident decisions in new product and material development.

This role is an opportunity to play a key role in advancing predictive modeling and advanced experimental strategy to accelerate the design and development of nextgeneration materials. Applying rigorous quantitative methods to enable informed decisionmaking early in technology and product development.

The role operates at the intersection of modeling, statistics, and machine learning, with a strong emphasis on translating these capabilities into practical approaches that support technology and innovation programs. This position also builds and deploys digital methods to guide experimentation, prediction, and optimization that support computer aided engineering and new product development efforts.

**Location can be hybrid in one of the following locations: 

  • Wilmington, DE
  • Florence, KY
  • Auburn Hills, MI
  • Irving, TX

Predictive Modeling for Material Property Design

  • Develop and apply predictive and hybrid machine learning approaches for the prediction of properties key to designing the next generation of materials.
  • Integrate mechanistic understanding, statistical modeling, and datadriven methods to generate reliable, decisionready predictions.
  • Quantify model confidence and limitations to support riskaware technical decisions.
  • Translate complex modeling outputs into clear, actionable insights for technology and innovation stakeholders.

Experimental Design & Bayesian Optimization for New Product Development

  • Design and apply advanced experimental design strategies and Bayesian optimization for new product development.
  • Efficiently explore highdimensional design spaces to prioritize experiments and identify optimal candidates for laboratory evaluation.
  • Apply adaptive and sequential learning approaches to balance exploration and exploitation under limited data conditions.

  • Master's Degree or higher, or with equivalent experience in computer science, computer engineering, machine learning, physics, applied mathematics or related field
  • Understanding of advanced materials, chemical processes, and laboratory data is a plus.
  • 1+ years' work experience with modeling development, data analysis, business communication, and digital transformation is highly desirable.
  • Proficiency in AI + physics-based machine learning.
  • Working understanding of material science fundamentals
  • Strong foundation in applied statistics, experimental design, and probabilistic modeling.
  • Expertise in predictive modeling and simulation for material or system property prediction.
  • Experience with uncertainty quantification, model validation, and decision support under uncertainty.
  • Ability to translate advanced quantitative methods into practical workflows including proof-of-concept full-stack (backend + frontend) applications that inform technology and product decisions.
  • Working across the full lifecycle: problem formulation → model and strategy development → application and adoption.
  • Communicating complex modeling and experimental concepts clearly to diverse technical audiences.
  • Influencing technology and innovation decisions through quantitative, modeldriven insight.
  • Operating effectively in crossfunctional environments spanning product development, technology, innovation, and digital teams.

Apply