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Data Science Entry Level Remote Jobs in Colorado

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific ... Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific ... Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific ... Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific ... Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

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Data Science Entry Level Remote information

What is a data science entry level remote job?

Data science entry level remote jobs are positions suitable for individuals who are just starting their careers in data science and prefer or require the flexibility to work from home or any location outside the traditional office setting. These roles typically involve tasks such as data cleaning, basic statistical analysis, creating simple data visualizations, and assisting with machine learning projects under supervision. Entry level data scientists often work closely with more experienced team members and use tools like Python, R, SQL, and Excel. Remote roles require good communication skills and self-motivation, as collaboration happens online. These positions are a great way to gain practical experience and develop technical skills in the field of data science.

What skills and qualifications are needed to thrive as an entry-level remote data scientist?

To thrive as an entry-level remote Data Scientist, you need a solid background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree or certification. Familiarity with tools like Jupyter Notebook, SQL databases, and machine learning libraries such as scikit-learn or TensorFlow is commonly required. Strong problem-solving abilities, communication skills, and self-motivation are crucial soft skills for remote collaboration and project management. These competencies enable effective data-driven insights, seamless teamwork, and measurable contributions in a distributed work environment.

What challenges do entry-level data scientists face when working remotely, and how can they overcome them?

Entry-level data scientists working remotely often encounter challenges such as limited access to mentorship, difficulty in collaborating on complex projects, and adjusting to asynchronous communication. To overcome these, it's important to proactively seek guidance from senior team members through regular check-ins, participate actively in team meetings and online forums, and document your work thoroughly for transparency. Leveraging collaborative tools like shared code repositories and communication platforms can also help maintain strong connections with your team and ensure project alignment.

What is the difference between Data Science Entry Level Remote vs Data Analyst Entry Level Remote?

AspectData Science Entry Level RemoteData Analyst Entry Level Remote
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentRemote, collaborative teams, often with cross-functional departmentsRemote, often working independently or with business teams
Employer & Industry UsageTech companies, finance, healthcare, e-commerceBusiness, marketing, finance, healthcare

While both roles are entry-level remote positions involving data, Data Science Entry Level Remote focuses on programming, machine learning, and predictive modeling, whereas Data Analyst Entry Level Remote emphasizes data visualization, reporting, and interpreting data for business insights. Candidates should choose based on their skills and career interests.

What are the most commonly searched types of Data Science Remote jobs in Colorado?

The most popular types of Data Science Remote jobs in Colorado are:

What are popular job titles related to Data Science Entry Level Remote jobs in Colorado?

For Data Science Entry Level Remote jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Data Science Entry Level Remote jobs?

Cities in Colorado with the most Data Science Entry Level Remote job openings:

Infographic showing various Data Science Entry Level Remote job openings in Colorado as of August 2026, with employment types broken down into 7% Internship, 69% Full Time, 15% Part Time, 2% Temporary, and 7% Contract. Highlights an 100% Remote job distribution.

$51K/yr

Full-time

Posted 13 days ago


U.S. Department Of Defense rating

7.8

Company rating: 7.8 out of 10

Based on 538 frontline employees who took The Breakroom Quiz

28th of 49 rated military and defense


Job description

Spectral Imagery Scientists process, analyze, and exploit spectral imagery to extract intelligence and geospatial information using advanced scientific methodologies, algorithms, and software tools. They collaborate with analysts to understand intelligence issues, provide scientific results to conduct intelligence production, and educate stakeholders on product capabilities. They develop, test, an

Qualifications:

MANDATORY QUALIFICATION CRITERIA: For this particular job, applicants must meet all competencies reflected under the Mandatory Qualification Criteria to include education (if required). Online resumes must demonstrate qualification by providing specific examples and associated results, in response to the announcement's mandatory criteria specified in this vacancy announcement:
Experience utilizing existing workflows or assisting in the development of techniques to process imagery, raster, and/or 3D data
Academic or professional experience applying fundamental concepts of imagery science, photogrammetry, spectroscopy, lidar/3D, multispectral, hyperspectral, SAR, and/or thermal image processing
Experience applying established remote sensing analytic techniques to assist in solving scientific or operational intelligence problems
Experience contributing to the development of written reports or briefings to communicate findings
Experience working with team members to complete assigned tasks
EDUCATION REQUIREMENT: A. Education: Bachelor's degree from an accredited college or university in Engineering, Imagery Science, Mathematics, Physical Science, Remote Sensing, Geography, Computer Science, Data Analytics, or a related discipline that included 24 semester hours in Physical Science and/or related Engineering Science such as Dynamics, Electronics, Mechanics, and Properties of Materials. -OR- B. Combination of Education and Experience: A minimum of 24 semester (36 quarter) hours of coursework in any area listed in option A that included at least 24 semester hours in Physical Science and/or related Engineering Science, plus experience that involves processing, analyzing, and exploiting multibanded imagery to extract intelligence and geospatial information, or a related field that demonstrates the ability to successfully perform the duties associated with this work. As a rule, every 30 semester (45 quarter) hours of coursework is equivalent to one year of experience. Candidates should show that their combination of education and experience totals 4 years.
PHYSICAL REQUIREMENT: Near visual acuity of 20/60 or better with or without corrective lenses

DESIRABLE QUALIFICATION CRITERIA: In addition to the mandatory qualifications, experience in the following is desired:
Academic or professional experience researching analytical techniques in published literature related to remote sensing
Knowledge of scripting languages (such as Python, R, or Matlab) for data processing or analysis
Familiarity with or academic exposure to how artificial intelligence, machine learning computer vision, and/or automated feature extraction concepts are applied to remote sensing
Experience assisting with the operation, calibration, or testing of satellite, airborne, and/or ground imaging systems and chemical analysis instruments
Knowledge of standard remote sensing processing tools (e.g., RemoteView, ENVI, SocetGXP, ARCGIS Pro, Google Earth Engine)

Education:Employment Type: OTHER

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