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Data Science Engineer Jobs in Colorado (NOW HIRING)

Data Scientist

Boulder, CO ยท On-site

$130K - $160K/yr

DEEP DIVE INTO THIS ROLE As a Data Scientist, you'll analyze large datasets, develop predictive models, and work with engineering teams to integrate your solutions into production. Key ...

Data Scientist - AI Products

Englewood, CO ยท On-site

$126K - $208K/yr

Bachelor's degree in Statistics, Machine Learning, Computer Science, Engineering, Mathematics, Physics, or a related quantitative field * 6+ years of experience in data science and applied machine ...

We are seeking a Data Scientist to support our NLP project focused on accurate and automatic ... Computer Science or a degree in a related field (Computer Information Systems, Engineering), a ...

Doctorate degree OR Master's degree and 2 years of Data Science or Engineering experience OR Bachelor's degree and 4 years of Data Science or Engineering experience OR Associate's degree and 8 years ...

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Data Science Engineer information

See Colorado salary details

$46.8K

$136.4K

$186.6K

How much do data science engineer jobs pay per year?

As of Jul 1, 2026, the average yearly pay for data science engineer in Colorado is $136,399.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,400.00 and $144,600.00 per year, depending on experience, location, and employer.

What engineers make 500,000?

Senior data science engineers, machine learning engineers, and software engineers with extensive experience and advanced skills in areas like AI, big data, and cloud computing can earn salaries of $500,000 or more, especially in high-cost-of-living regions or within top tech companies. Achieving this level often requires advanced degrees, certifications, and a strong track record of impactful projects.

Is 30 too late for data science?

Data Science Engineers can enter the field at any age, including 30, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

What are the key skills and qualifications needed to thrive in the Data Science Engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What are the typical daily responsibilities of a Data Science Engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

What is a Data Science Engineer job?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What does a data science engineer do?

A data science engineer designs, develops, and maintains data pipelines and infrastructure to support data analysis and machine learning models. They work with large datasets, use programming languages like Python or Scala, and often collaborate with data scientists and software engineers to ensure data quality and accessibility.

Is data science high paying?

Data science engineers typically earn high salaries due to their specialized skills in statistical analysis, programming, and machine learning. Salaries vary by experience, location, and industry, but data science roles are generally considered well-compensated within the tech field.
What are the most commonly searched types of Data Science Engineer jobs in Colorado? The most popular types of Data Science Engineer jobs in Colorado are:
What are popular job titles related to Data Science Engineer jobs in Colorado? For Data Science Engineer jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Data Science Engineer jobs in Colorado look for? The top searched job categories for Data Science Engineer jobs in Colorado are:
What cities in Colorado are hiring for Data Science Engineer jobs? Cities in Colorado with the most Data Science Engineer job openings:
Infographic showing various Data Science Engineer job openings in Colorado as of June 2026, with employment types broken down into 1% As Needed, 92% Full Time, 6% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $136,399 per year, or $65.6 per hour.
Graduate (Year-Round) Intern: Geospatial Data Science Modeling and Analysis

Graduate (Year-Round) Intern: Geospatial Data Science Modeling and Analysis

The National Renewable Energy Laboratory (NREL)

Golden, CO โ€ข On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 16 hours ago


Job description

Posting Title
Graduate (Year-Round) Intern: Geospatial Data Science Modeling and Analysis
Location
CO - Golden
Position Type
Intern (Fixed Term)
Hours Per Week
40
Working at NLR
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.
Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
Job Description
The Geospatial Data Science (GDS) team within the Strategic Energy Analysis Center at the National Laboratory of the Rockies (NLR) is seeking a 6-12-month intern to support modeling and analysis. The GDS group conducts research at the intersection of energy deployment, big data science, and geospatial modeling and visualization. Our team of researchers develops and applies geospatial algorithms and methods to evaluate the deployment potential for energy technologies, including geothermal, hydropower, transmission, bioenergy, wind, and solar. Geospatial modeling at NLR enables detailed techno-economic assessment, capacity expansion, and power systems modeling of energy resources under a variety of regulatory, sociopolitical, and environmental factors from local to continental scales.
The successful intern candidate will support a large and diverse modeling portfolio with activities involving geospatial analyses, literature reviews, cartography, scientific programming, and tasks focused on data preparation, processing, and validation. This position will assist geospatial scientists in developing novel analytical solutions to complex challenges in energy siting, deployment, and adoption. Candidates should be interested in working in an interdisciplinary field, together with geospatial data scientists, software developers, and policy analysts, which will require excellent interpersonal and communication skills.
Duties will include:
  • Manipulating multiple data sources, models, and software tools with scientific and engineering workflows for decision support and data analysis
  • Preparing and processing geospatial data using open-source desktop software and programmatic approaches
  • Conducting background research on data sets, current modeling approaches, and existing tools
  • Developing literature reviews under the guidance of research scientists
  • Programming and scripting in Python to conduct analysis and visualize data
  • Working in distributed computing environments including internal servers, NLR's high-performance computing (HPC) system and the Cloud

Basic Qualifications
Minimum of a 3.0 cumulative grade point average.
Undergraduate: Must be enrolled as a full-time student in a bachelor's degree program from an accredited institution.
Post Undergraduate: Earned a bachelor's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate: Must be enrolled as a full-time student in a master's degree program from an accredited institution.
Post Graduate: Earned a master's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master's degree and enrolled as PhD student from an accredited institution.
Please Note:
โ€ข Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process.
โ€ข If selected for position, a letter of recommendation will be required as part of the hiring process.
โ€ข Must meet educational requirements prior to employment start date.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
  • Must have completed a bachelor's degree and either: be enrolled in or recently graduated from a master's degree or currently enrolled in a PhD program in fields such as: Geography/GIS, Environmental Science, Computer Science, Engineering, or a related technical field
  • To be considered, all candidates must include in their resume and an online code repository such as GitHub with several publicly visible coding projects. Alternatively, please explain in your cover letter why your application does not include a code repository and/or several examples of previous projects
  • Demonstrated experience working independently with programming skills in python and libraries such as geopandas, numpy, scipy, shapely, pyproj
  • Proficiency and experience with geospatial analysis and modeling techniques using open-source tools, such as QGIS; (please note that ESRI tools are not used in this research group)
  • Experience working with geographic transformations and projections
  • Ability to work within a dynamically evolving digital environment as a member of collaborative and often-dispersed team
  • Critical thinking skills; analytic and research skills; written and verbal communication skills

Preferred Qualifications
  • Experience with linux/unix
  • Experience with collaborative code development
  • Experience with Machine Learning
  • Experience with the Geospatial data abstraction library (GADL)
  • Experience with big geospatial data processing

Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: / Annual Salary Range: $44,500 - $71,200
NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.
Benefits Summary
Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.
* Based on eligibility rules
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.
Drug Free Workplace
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Submission Guidelines
Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Reasonable Accommodations
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