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Environmental Statistician Jobs in Oregon (NOW HIRING)

Senior Data Scientist

OR ยท On-site +1

$140K - $190K/yr

... of statistical models and machine learning algorithms to improve patient enrollment and trial management. You'll work in a highly regulated healthcare data environment, ensuring compliance with ...

Title: Adjunct Instructor in Environmental Science Department: Department of Chemistry and ... statistics for the most recent three year period is available on the NJIT Department of Public ...

At least 3 years practical experience designing and executing statistical analyses in a regulated environment and clinical trials for regulatory submissions * Minimum of 4 years practical experience ...

Senior Director, Biostatistics

OR ยท On-site +1

$290K/yr

The selected individual will be responsible for statistical activities supporting clinical trials ... Ability to work collaboratively in a multidisciplinary team environment. What We Offer

Statistical programming experience in a clinical development environment * Experience working effectively in a globally dispersed team environment with cross-cultural partners * Ability to lead and ...

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Environmental Statistician information

See Oregon salary details

$53.4K

$91.9K

$123.2K

How much do environmental statistician jobs pay per year?

As of Sep 8, 2026, the average yearly pay for environmental statistician in Oregon is $91,900.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,800.00 and $104,100.00 per year, depending on experience, location, and employer.

What does an environmental statistician do?

An Environmental Statistician applies statistical methods to environmental science issues, such as analyzing data on air and water quality, climate change, and ecosystem health. They design experiments, collect and interpret data, and help inform policy decisions by providing scientific evidence. Their work supports understanding environmental trends and assessing the effectiveness of environmental regulations. Environmental Statisticians may collaborate with scientists, government agencies, and industries to address environmental challenges.

What does an environmental statistician do?

An environmental statistician interprets and analyzes data related to the environment. Your job duties include working on a broad range of topics for a company, a government agency, research organization, or nonprofit entity. Your analysis duties can focus on climate, pollution, animal populations, or data from environmental samples. As a statistician, you often use a mathematical model to forecast future environmental conditions. Your responsibilities usually include creating a report that explains your research or forecasts. In addition to applying statistical analysis to environmental issues, you also manage databases containing the information that you use for your work.

What are the key skills and qualifications needed to thrive as an environmental statistician, and why are they important?

To excel as an Environmental Statistician, you need a solid background in statistics, mathematics, and environmental science, usually supported by at least a master's degree in statistics or a related field. Proficiency in statistical software such as R, SAS, or Python, as well as experience with GIS systems and data modeling tools, is typically required. Attention to detail, problem-solving skills, and the ability to communicate complex results to non-technical stakeholders help set top performers apart. These skills are essential for accurately analyzing environmental data and informing critical decisions about environmental policy and management.

What are some common challenges faced by environmental statisticians when working with real-world ecological data?

Environmental statisticians often encounter challenges such as dealing with incomplete or irregularly collected data, spatial and temporal variability, and integrating data from multiple sources. Real-world ecological data can be noisy and may require advanced statistical techniques to identify meaningful trends. Collaborating closely with environmental scientists and field researchers is essential for understanding the context of the data and ensuring that statistical models accurately reflect ecological processes.

What is the difference between Environmental Statistician vs Environmental Data Analyst?

AspectEnvironmental StatisticianEnvironmental Data Analyst
Required CredentialsBachelor's or master's in statistics, environmental science, or related fields; proficiency in statistical softwareBachelor's or master's in environmental science, data analysis, or related fields; skills in data visualization and analysis tools
Work EnvironmentResearch institutions, government agencies, environmental consulting firmsEnvironmental organizations, government agencies, private companies
Employer & Industry UsageUsed for designing studies, analyzing environmental data, and statistical modelingUsed for interpreting environmental data, creating reports, and supporting decision-making

While both roles involve analyzing environmental data, Environmental Statisticians focus on designing studies and applying advanced statistical methods, whereas Environmental Data Analysts primarily interpret data and generate reports to inform environmental decisions.

What are the most commonly searched types of Environmental Statistician jobs in Oregon?

The most popular types of Environmental Statistician jobs in Oregon are:

What are popular job titles related to Environmental Statistician jobs in Oregon?

For Environmental Statistician jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Environmental Statistician jobs in Oregon look for?

The top searched job categories for Environmental Statistician jobs in Oregon are:

Infographic showing various Environmental Statistician job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 16% Part Time, 1% Contract, and 1% Nights. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $91,900 per year, or $44.2 per hour.

Senior Data Scientist

OneStudyTeam

OR โ€ข On-site, Remote

$140K - $190K/yr

Full-time

Re-posted 27 days ago


Key responsibilities

  • Develop and enhance statistical models and machine learning algorithms to improve patient enrollment, site randomization forecasting, and trial management.

  • Support projects to build algorithms for patient matching and ranking to enhance recruitment efficiency.

  • Build and optimize data pipelines and analytical workflows to enable scalable model training and deployment.


Job description

As a Senior Data Scientist, you will play a pivotal role in advancing Reify Health's data-driven solutions for clinical trials. In this position, you will drive the development of statistical models and machine learning algorithms to improve patient enrollment and trial management. You'll work in a highly regulated healthcare data environment, ensuring compliance with privacy standards while innovating on predictive analytics. This role involves close collaboration with cross-functional teams (especially ML Engineering) to translate complex data insights into practical, impactful tools for the clinical research community.

What You'll Be Working On
  • Site Randomization Forecasting: Develop/enhance forecasting models for site randomization and enrollment trends, enabling better planning and resource allocation across trial sites.ย 
  • Patient Matching/Ranking Algorithms: Support projects to build algorithms that intelligently match patients to (or rank patients for) appropriate clinical trials, enhancing recruitment efficiency and patient inclusion.ย 
  • Develop Other Advanced Statistical Models: Create and refine predictive models (Bayesian inference, regression analysis, time-series forecasting) to address other key clinical trial challenges and improve decision-making.ย 
  • AI Monitoring and Bias Detection: Implement processes to monitor machine learning models in production, detecting bias or performance drift and ensuring models remain fair, accurate, and compliant.ย 
  • Data Pipeline & Tooling Development: Build and optimize data pipelines and analytical workflows using tools like AWS Athena, Redshift, SageMaker, and dbt, enabling scalable model training and deployment.ย 
  • Regulatory Compliance in Data Science: Ensure all data science practices align with HIPAA, GDPR, and other privacy regulations, integrating compliance considerations into model development and data handling.ย 
  • Cross-Functional Collaboration: Work closely with machine learning engineers, product managers, and other stakeholders to integrate models into products and clearly communicate insights and recommendations.ย 
What You Bring to OneStudyTeam
  • Minimum Education:
    • Minimum of Master's or Ph.D. in Statistics, Data Science, Computer Science, or a related quantitative field (or equivalent professional experience).ย 
  • Minimum Experience:
    • Minimum of 5+ years of hands-on data science or analytics experience, preferably in a healthcare, clinical research, or other highly regulated data environment.
  • Statistical & ML Expertise: Strong foundation in statistical modeling and machine learning techniques, including experience with Bayesian methods, regression analysis, and time-series forecasting.ย 
  • Model Monitoring & Fairness: Proficiency in evaluating model performance and bias, with the ability to implement AI monitoring tools and bias mitigation strategies to ensure ethical and reliable outcomes.ย 
  • Technical Toolset: Advanced programming skills in Python (with libraries such as scikit-learn, PyMC, mlforecast, etc.) and SQL, as well as familiarity with data transformation tools like dbt.ย 
  • Cloud & Data Infrastructure: Hands-on experience with cloud-based analytics and ML services, especially AWS tools (Athena for querying, Redshift for data warehousing, SageMaker for model development/deployment).ย 
  • Regulated Data Handling: Experience working with sensitive healthcare or clinical trial data under regulations like HIPAA and GDPR, demonstrating a deep commitment to data privacy and security best practices.ย 
  • Collaborative Communication: Excellent teamwork and meticulous verbal/written communication abilities, with a track record of partnering with engineering and product teams to translate data science work into actionable business solutions.ย 
  • Domain Knowledge: Understanding of clinical research or health-tech environments is highly valuable, including insight into clinical trial operations and a passion for improving patient outcomes through data.

The expected pay range for this role is $140,000 - $190,000 USD per year for full time team members.

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