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Statistical Engineering Jobs in Colorado (NOW HIRING)

Quantix

C# Engineer Lead

Centennial, CO · On-site

$105K - $138K/yr

... statistical analysis. 3) Heavy data background. 4) Strong mathematical / algorithm skills. 5) Lead experience. 6) Bachelors degree. Desired Skills: 1) Computer science, mathematics or engineering ...

Electra

Principal Data Scientist (Boulder)

Boulder, CO · On-site

$175K - $215K/yr

Bachelor's degree in computer science, statistics, engineering, or related fields * 15+ years of experience in applied data science for complex engineered systems, with a focus on reliability ...

Electra

Principal Data Scientist

Boulder, CO · On-site

$175K - $215K/yr

Bachelor's degree in computer science, statistics, engineering, or related fields * 15+ years of experience in applied data science for complex engineered systems, with focus on reliability modeling ...

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All JobsStatistical Engineering JobsStatistical Engineering Jobs in Colorado

Statistical Engineering information

See Colorado salary details

$61.2K

$71.8K

$80.2K

How much do statistical engineering jobs pay per year?

As of Jul 7, 2026, the average yearly pay for statistical engineering in Colorado is $71,834.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,700.00 and $76,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Statistical Engineer, and why are they important?

To thrive as a Statistical Engineer, you need strong quantitative analysis skills, a background in statistics or mathematics, and often a relevant degree such as in engineering or applied statistics. Proficiency with statistical software (e.g., R, SAS, Python), data management systems, and sometimes Six Sigma certification is typically required. Critical thinking, problem-solving, and clear communication are crucial soft skills for interpreting data and collaborating with multidisciplinary teams. These skills ensure accurate data-driven decisions, efficient process improvements, and effective solutions to complex engineering challenges.

What is the difference between Statistical Engineering vs Data Scientist?

AspectStatistical EngineeringData Scientist
Required credentialsStatistics, Data Analysis, EngineeringStatistics, Computer Science, Data Analysis
Work environmentManufacturing, R&D, Engineering teamsBusiness, Tech, Research sectors
Employer usageOptimizing processes, designing experimentsBuilding models, insights, predictive analytics

Statistical Engineering focuses on applying statistical methods to improve engineering processes and product development, often within manufacturing or R&D settings. Data Scientists analyze large datasets to extract insights, build predictive models, and support business decisions. While both roles require strong statistical skills, Statistical Engineering emphasizes process optimization and experimental design, whereas Data Scientists focus on data-driven insights across diverse industries.

How does a Statistical Engineer typically collaborate with cross-functional teams to implement data-driven solutions?

Statistical Engineers frequently work alongside data scientists, software engineers, and business analysts to design and implement robust data-driven solutions. They are responsible for translating complex statistical models into actionable insights and ensuring that these models are integrated effectively within existing systems. Collaboration often involves regular meetings to align on project goals, sharing progress updates, and troubleshooting technical challenges together. This interdisciplinary teamwork is essential for ensuring that statistical methodologies are not only theoretically sound but also practically applicable to real-world business problems.

What is statistical engineering?

Statistical engineering is an interdisciplinary field that focuses on the integration and application of statistical methods and principles to solve complex, large-scale problems in science, business, and engineering. It involves designing data collection processes, analyzing and interpreting data, and implementing statistical solutions within larger systems. Statistical engineers often work on projects that require collaboration with other engineering disciplines, using statistics as a foundational tool to drive decision-making and innovation.
What are popular job titles related to Statistical Engineering jobs in Colorado? For Statistical Engineering jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Statistical Engineering jobs in Colorado look for? The top searched job categories for Statistical Engineering jobs in Colorado are:
What cities in Colorado are hiring for Statistical Engineering jobs? Cities in Colorado with the most Statistical Engineering job openings:
Statistical Engineering jobs near you
Infographic showing various Statistical Engineering job openings in Colorado as of July 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $71,834 per year, or $34.5 per hour.
Interdisciplinary Biologist (Computational) / Mathematical Statistician

Interdisciplinary Biologist (Computational) / Mathematical Statistician

U.S. Department of Agriculture (USDA)

Denver, CO • On-site, Remote

$99K/yr

Other

Posted 7 days ago

Job description

In this position, you will be protecting agriculture, property, natural resources (including rare or special species), and reducing conflicts that jeopardize human health and safety. The overall goal of the position is to develop statistical decision-support tools for the feral swine and wildlife disease management of Wildlife Services.Qualifications:Applicants must meet all qualifications and eligibility requirements by the closing date of the announcement, including specialized experience and/or education, as defined below.
BASIC REQUIREMENT for 0401 Series: Degree: biological sciences, agriculture, natural resource management, chemistry, or related disciplines appropriate to the position. OR Combination of education and experience: Courses equivalent to a major, as shown above, plus appropriate experience or additional education.
BASIC REQUIREMENT for 1529 Series: Degree: that included 24 semester hours of mathematics and statistics, of which at least 12 semester hours were in mathematics and 6 semester hours were in statistics. OR Combination of education and experience: at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as shown above, plus appropriate experience or additional education.
FOR THE GS-12 LEVEL: Applicants must have one year of specialized experience (equivalent to the GS-11 grade level) that demonstrates:
- Communicates technical information both orally and in writing to stakeholders for collaborative development of research or software development projects.
- Develops data pipelines for extracting environmental data (e.g., GIS rasters, satellite imagery/remote sensing, landcover, weather/meteorological data) with automated post-processing for inputs into downstream modeling or visualizations.
- Builds custom statistical (prefer hierarchical statistical models using Bayesian techniques) models or computational biology models, or bioinformatic and phylogenetic workflows using computer programming.
- Develops machine learning or artificial intelligence models for image processing or predicting ecological or epidemiological processes.
- Uses programming languages in at least two data science areas such as: statistics (e.g., C++, python, or R), software or web application development (e.g., JavaScript or HTML), database management (e.g., SQL), managing HPC workflows (e.g., SLURM) or cloud platforms (e.g., AWS, Azure, or GCP).
Note: There is no education substitution for this grade level.
TRANSCRIPTS are required if:
  • This position requires specific coursework or a degree in a specific field to be basically qualified.
  • You are qualifying for this position based on a combination of experience and education.
  • This education must have been successfully completed and obtained from an accredited school, college, or university.
Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional, philanthropic, religious, spiritual, community, student, social). Volunteer work helps build critical competencies and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.Education:Please see above for education qualification requirement information.Employment Type: OTHER

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