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How much do regression analysis jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for regression analysis in the United States is $32.41, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $37.02 per hour, depending on experience, location, and employer.

What is regression analysis?

A Regression Analysis job involves analyzing data to identify relationships between variables and make predictions. Professionals in this field use statistical techniques, such as linear and logistic regression, to interpret trends and patterns. They often work with large datasets, using tools like Python, R, or Excel to build models that support business decisions. These roles are common in industries like finance, healthcare, and marketing, where data-driven insights are crucial.

What are the typical responsibilities and challenges faced by professionals specializing in regression analysis?

Professionals in regression analysis are primarily responsible for collecting and cleaning data, selecting appropriate statistical models, running regression tests, and interpreting results for actionable insights. One of the key challenges in this role is ensuring the accuracy and validity of models when handling large, complex, or incomplete datasets, as well as communicating technical outcomes to non-technical stakeholders. These roles often involve close collaboration with data scientists, business analysts, and decision-makers to tailor analyses to specific organizational needs. By translating data patterns into understandable recommendations, regression analysts play a vital role in supporting company strategy and operational improvements.

What are the key skills and qualifications needed to thrive in regression analysis, and why are they important?

Excelling in Regression Analysis requires a solid background in statistics, mathematics, and data interpretation, typically supported by a degree in statistics, mathematics, data science, or a closely related field. Familiarity with analytical tools and programming languages such as R, Python, SAS, or SPSS, and knowledge of data visualization platforms are highly valuable. Strong analytical thinking, attention to detail, and effective communication skills enable clear presentation of complex findings to diverse stakeholders. These competencies are vital for drawing reliable predictive insights, shaping data-driven business decisions, and collaborating seamlessly within multidisciplinary teams.

Is regression analysis a skill?

Regression analysis is considered a technical skill used in data analysis and statistical modeling. Proficiency typically involves understanding statistical concepts, using tools like Excel, R, or Python, and interpreting results accurately. It is often listed as a required skill in roles such as data analyst, data scientist, or quantitative analyst.

What jobs use regression analysis?

Regression analysis is used in a variety of jobs including data analysts, statisticians, financial analysts, marketing analysts, and research scientists. These roles involve analyzing data to identify trends, make predictions, and support decision-making, often using tools like Excel, R, or Python. Strong analytical skills and understanding of statistical methods are essential in these positions.
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What states have the most Regression Analysis jobs?

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Regression Analysis jobs near you
Infographic showing various Regression Analysis job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $67,422 per year, or $32.4 per hour.

Biostatistician (Remote | $120-$170/hr)

Synthires

Moreno Valley, CA • On-site

$120 - $170/hr

Other

Posted 5 days ago

Job description


Biostatistician


Position: Biostatistician


Type: Contract


Compensation: $120–$170/hour


Location: Remote


About the Opportunity

This opportunity is for experienced Biostatisticians with expertise in biostatistics, clinical research, statistical modeling, study design, data analysis, and regulatory standards to contribute to advanced AI research and evaluation projects.

In this role, you'll apply your expertise to evaluate complex statistical analyses, clinical research methodologies, study designs, and AI-generated scientific outputs. Your work will help improve the accuracy, reasoning, and analytical capabilities of next-generation AI systems.

No prior AI experience is required. Your biostatistical expertise, methodological rigor, clinical interpretation, and regulatory knowledge are the primary qualifications for success in this role.

Responsibilities

  • Evaluate AI-generated biostatistical analyses, clinical research outputs, and statistical methodologies for accuracy and scientific rigor.
  • Apply expertise in study design, hypothesis testing, regression analysis, survival analysis, and statistical modeling.
  • Analyze clinical trial data, observational studies, epidemiological data, and healthcare datasets.
  • Review experimental designs, statistical analysis plans, endpoints, sample size calculations, and data interpretation.
  • Assess the appropriateness of statistical methods, assumptions, models, and analytical approaches.
  • Identify methodological errors, statistical inconsistencies, biases, and potential limitations in analyses.
  • Translate complex biostatistical concepts and research findings into clear, structured documentation for AI training and evaluation.
  • Apply professional judgment to ensure methodological rigor, clinical relevance, regulatory sensitivity, and statistical accuracy.

Required Qualifications

  • Master's degree or higher in Biostatistics, Statistics, Epidemiology, Public Health, Mathematics, or a related quantitative discipline.
  • Strong experience in biostatistical analysis, clinical research, healthcare research, or pharmaceutical research.
  • Expertise in statistical modeling, hypothesis testing, regression analysis, survival analysis, and experimental design.
  • Experience analyzing clinical trials, observational studies, or real-world healthcare data.
  • Proficiency in statistical software such as R, SAS, Python, SPSS, or Stata.
  • Strong understanding of clinical research methodologies, data interpretation, and statistical reporting.
  • Excellent analytical, problem-solving, written, and verbal communication skills.
  • Ability to work independently in a fully remote environment.

Preferred Qualifications

  • PhD in Biostatistics, Statistics, Epidemiology, Public Health, or a related field.
  • Experience working with clinical trials, pharmaceutical research, medical research, or regulatory submissions.
  • Familiarity with FDA, EMA, ICH, GCP, or other relevant regulatory guidelines.
  • Experience developing statistical analysis plans, clinical study protocols, or research evaluation frameworks.
  • Experience with machine learning, healthcare analytics, AI model evaluation, or scientific data annotation.
  • Experience collaborating with cross-functional, clinical, research, or remote teams.

Compensation

  • Competitive compensation of $120–$170/hour.
  • Weekly payments.
  • Independent contractor engagement.

Application Process

  1. Easy Apply on LinkedIn
  2. Check Email for Next Steps
  3. Participate in Resume Evaluation & Interview Stage


Apply