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Part Time Data Analyst R Programming Jobs in Colorado

... analysis. * Evaluate and synthesize findings from biological, chemical, and clinical data sources ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

... analysis. * Evaluate and synthesize findings from biological, chemical, and clinical data sources ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

... analysis. * Evaluate and synthesize findings from biological, chemical, and clinical data sources ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

... analysis. * Evaluate and synthesize findings from biological, chemical, and clinical data sources ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

... analysis. * Evaluate and synthesize findings from biological, chemical, and clinical data sources ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

... analysis. * Evaluate and synthesize findings from biological, chemical, and clinical data sources ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

Showing results 41-60

Part Time Data Analyst R Programming information

What is the difference between Part Time Data Analyst R Programming vs Part Time Data Analyst Python?

AspectPart Time Data Analyst R ProgrammingPart Time Data Analyst Python
Required SkillsProficiency in R, data visualization, statistical analysisProficiency in Python, data manipulation, machine learning
Work EnvironmentData analysis, reporting, statistical modelingData analysis, automation, machine learning projects
Industry UsageResearch, healthcare, financeTech, finance, marketing

Both roles involve data analysis in a part-time setting but differ mainly in programming language expertise. R is favored for statistical analysis and visualization, while Python is preferred for automation and machine learning tasks. Your choice depends on the specific tools and industry focus.

Do part time data analysts use R programming?

Part time data analysts often use R programming to perform data analysis, statistical modeling, and visualization tasks. Proficiency in R can enhance their ability to handle large datasets and deliver insights efficiently, making it a valuable skill for flexible or part time roles in data analysis.

Are R programmers in demand?

R programmers, including those with expertise in R programming for data analysis, are in demand across industries such as finance, healthcare, and technology due to the growing need for data-driven decision making. Skills in statistical analysis, data visualization, and familiarity with tools like RStudio increase employability in this field.
What are the most commonly searched types of Data Analyst R Programming jobs in Colorado? The most popular types of Data Analyst R Programming jobs in Colorado are:
What job categories do people searching Part Time Data Analyst R Programming jobs in Colorado look for? The top searched job categories for Part Time Data Analyst R Programming jobs in Colorado are:
What cities in Colorado are hiring for Part Time Data Analyst R Programming jobs? Cities in Colorado with the most Part Time Data Analyst R Programming job openings:

Digital Chemistry Specialist - Remote

micro1 AI

Colorado Springs, CO • Remote

$90 - $120/hr

Part-time

Posted 10 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 — 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.