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Remote Data Science R Jobs in Colorado (NOW HIRING)

... e.g., Python, R, RDKit, KNIME). * Strong scientific communication skills, with the ability to ... data science. * Experience collaborating in multidisciplinary or remote project environments is ...

... e.g., Python, R, RDKit, KNIME). * Strong scientific communication skills, with the ability to ... data science. * Experience collaborating in multidisciplinary or remote project environments is ...

... e.g., Python, R, RDKit, KNIME). * Strong scientific communication skills, with the ability to ... data science. * Experience collaborating in multidisciplinary or remote project environments is ...

... e.g., Python, R, RDKit, KNIME). * Strong scientific communication skills, with the ability to ... data science. * Experience collaborating in multidisciplinary or remote project environments is ...

Data Analyst Senior

Denver, CO ยท On-site +1

$107K - $155K/yr

... language like R or Python. The Data Analyst Senior cleans up data for analysis and/or visual ... Degree in Business, Accounting, Finance, Economics, Analytics, or Data Science is preferred. Our ...

This is a remote based position.** GENERAL SUMMARY OF DUTIES: Design, build, and maintain UDR ... EDUCATION AND EXPERIENCE: 1. Bachelor's degree in computer science, data science, data engineering ...

Senior Data Platform Engineer

Littleton, CO ยท Remote

$130K - $170K/yr

This is a remote based position.** GENERAL SUMMARY OF DUTIES: Design, build, and maintain UDR ... EDUCATION AND EXPERIENCE: 1. Bachelor's degree in computer science, data science, data engineering ...

Showing results 21-40

Remote Data Science R information

What is the difference between Remote Data Science R vs Remote Data Analyst?

AspectRemote Data Science RRemote Data Analyst
Required SkillsStatistical analysis, R programming, data modeling, machine learningData visualization, basic statistical analysis, Excel, SQL
CertificationsR certifications, data science certificates, possibly advanced degreesData analysis certifications, Excel, SQL courses
Work EnvironmentCollaborative teams, research projects, data science platformsReporting, dashboards, business insights
Industry UsageTech, finance, healthcare, research institutionsMarketing, retail, finance, operations

Remote Data Science R roles focus on advanced statistical modeling and machine learning using R, often requiring specialized certifications and working on complex data projects. Remote Data Analysts typically handle data reporting, visualization, and basic analysis to support business decisions. While both roles involve data handling, Data Science R positions demand deeper technical expertise and programming skills.

What is a remote data science R?

Remote Data Science R jobs are positions that involve using the R programming language to analyze and interpret data, build statistical models, and generate insights, all while working from a remote location. These roles typically require strong skills in data manipulation, visualization, and statistical analysis using R. Professionals in these positions may work for companies in various industries, collaborating with teams online and leveraging cloud-based tools. Remote Data Science R jobs offer flexibility, allowing individuals to work from home or anywhere with a reliable internet connection.

What are the key skills and qualifications needed to thrive as a remote data science R, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, expertise in statistics, programming (Python or R), and typically a degree in data science, computer science, or a related field. Familiarity with data analysis tools, machine learning frameworks (like TensorFlow or scikit-learn), and cloud platforms (such as AWS or Google Cloud) is commonly required. Outstanding problem-solving, self-motivation, and effective virtual communication skills help you excel in remote environments. These abilities are essential for deriving actionable insights from data and collaborating efficiently across distributed teams.

How do remote data science R professionals typically collaborate with cross-functional teams while working from different locations?

Remote Data Science R professionals often use a combination of communication platforms (like Slack, Microsoft Teams, or Zoom) and project management tools (such as Jira or Trello) to stay connected with colleagues in engineering, product management, and business analysis. Sharing code and models through version control systems (like Git) and documenting workflows in shared repositories helps maintain transparency and collaboration. Regular virtual meetings and presentations are crucial for aligning goals, discussing progress, and receiving feedback. This collaborative approach ensures that data-driven insights effectively support organizational objectives, even in a distributed work environment.
What are the most commonly searched types of Data Science R jobs in Colorado? The most popular types of Data Science R jobs in Colorado are:
What are popular job titles related to Remote Data Science R jobs in Colorado? For Remote Data Science R jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Remote Data Science R jobs? Cities in Colorado with the most Remote Data Science R job openings:

AI Training Specialist - Life Sciences

micro1 AI

Boulder, CO โ€ข Remote

$90 - $120/hr

Part-time

Posted 9 days ago


Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required โ€” your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.