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Remote Data Science R Jobs in Colorado (NOW HIRING)

Lynker Corporation

Environmental Data Scientist

Boulder, CO · On-site +1

$75K - $105K/yr

Proficiency in a data science language such as R or Python for data wrangling, analysis, and modeling. * A working sense of geospatial data science, including experience with GIS tooling and spatial ...

NuView

Data Analyst

Denver, CO · On-site +1

$80K - $100K/yr

Salary: $80k-100K + bonus + benefits Location: 100% remote for US-based candidates Responsibilities ... Science or a related Field * 1-3 Years of Relevant job experience * SQL Required * R or Python ...

NuView Analytics

Data Analyst

Denver, CO · Remote

$80K - $100K/yr

Salary: $80k-100K + bonus + benefits Location: 100% remote for US-based candidates Responsibilities ... Science or a related Field * 1-3 Years of Relevant job experience * SQL Required * R or Python ...

NuView Analytics

Senior Data Analyst

Denver, CO · Remote

$90K - $120K/yr

100% Remote Full-time Senior Analyst At NuView Analytics - we help companies accelerate the time to ... Science or a related Field * 3-5 Years of Relevant job experience * SQL Required * R or Python ...

NuView

Senior Data Analyst

Denver, CO · On-site +1

$90K - $120K/yr

100% Remote Full-time Senior Analyst At NuView Analytics - we help companies accelerate the time to ... Science or a related Field * 3-5 Years of Relevant job experience * SQL Required * R or Python ...

Averna

Data Analyst

Denver, CO · Remote

Bachelor's degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics ... SQL, Python, R). * Proven experience creating dashboards, reports, and structured datasets to ...

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All JobsData Science R JobsRemote Data Science R JobsRemote Data Science R Jobs in Colorado

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 job categories do people searching Remote Data Science R jobs in Colorado look for? The top searched job categories for Remote Data Science R jobs in Colorado 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:
Remote Data Science R jobs near you

Environmental Data Scientist

Lynker Corporation

Boulder, CO • On-site, Remote

$75K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago

Job description

Overview
Lynker Corporation is a leading provider of innovative solutions in weather and climate science. With a commitment to excellence and a passion for innovation, Lynker leverages cutting-edge technologies and scientific expertise to support the creation and delivery of improved operational weather forecasts.
As part of our ongoing growth and expansion, we are seeking a dynamic and experienced Environmental Data Scientist to join our growing team.
Responsibilities
Duties of the Environmental Data Scientist will include the following:
  • Data organization: organize, catalog, and structure heterogeneous environmental and geospatial datasets using consistent metadata and controlled vocabularies, with clear provenance, so they can be combined consistently and reproducibly.
  • Analytical logic: help define how rules and analytical logic are represented, versioned, and evaluated against layered datasets, with traceable analytical lineage from inputs to results.
  • Data product design: define what analytical inputs and outputs should contain, including data, results, and metadata, the schemas that represent them, and how those schemas evolve over time.
  • Domain reasoning: bring environmental and hydrologic domain knowledge to bear on how data is weighted, interpreted, and encoded into rules.
  • Validation & QA: develop checks, test cases, and validation logic to confirm that rules produce correct, explainable, and consistent results.
  • Documentation & collaboration: document data schemas, analytical logic, and data sources; collaborate across the Science, Engineering, and Platform teams to keep the system understandable, accessible, and maintainable.

Qualifications
The Environmental Data Scientist selected should have the following:
  • Master's in environmental science, ecosystem science, water resources, hydrology, earth science, environmental data science, or a related field; or a Bachelor's plus 2 years applying data science to environmental problems; or equivalent hands-on experience.
  • Strong environmental and data science background, with the ability to reason about how environmental evidence should be represented and combined.
  • Proficiency in a data science language such as R or Python for data wrangling, analysis, and modeling.
  • A working sense of geospatial data science, including experience with GIS tooling and spatial datasets (e.g., R, ArcGIS, QGIS, Google Earth Engine).
  • Comfort thinking structurally about data schemas, inputs, and outputs, and translating domain logic into clear, testable rules.
  • Strong technical and scientific writing skills.

The Ideal Environmental Data Scientist will have the following:
  • Experience designing data schemas, structured formats, or APIs, and defining inputs and outputs for downstream consumers.
  • Familiarity with rules-based or decision-support systems and how to make their logic transparent and explainable.
  • Experience integrating multiple public and agency data sources (e.g., USGS, NOAA, PRISM) for watershed or environmental analysis.
  • Exposure to machine learning or statistical modeling applied to environmental data.
  • Track record of scientific writing, publication, or open-source contribution.
  • Colorado Front Range presence for periodic in-person collaboration.

About Lynker
Lynker is a growing, employee owned business, specializing in professional, scientific and technical services. Our continually expanding team combines scientific expertise with mature, results-driven processes and tools to achieve technically sound, cost effective solutions in hydrology/water sciences, geospatial analysis, information technology, resource management, conservation, and management and business process improvement.
We focus on putting the right people in the right place to be effective. And having the right people is critical for success. Our streamlined organization enables and empowers our talented professionals to tackle our customers' scientific and technical priorities - creatively and effectively.
Lynker offers a team-oriented work environment, and the opportunity to work in a culture of exceptionally skilled professionals who embrace sound science and creative solutions. Lynker's benefits include the following:
  • Comprehensive healthcare for the employee at no monthly cost
  • Healthcare benefit covers medical, prescription drug, dental, and vision
  • Personal Time Off (PTO) Policy plus paid holidays
  • Highly competitive compensation plan regularly calibrated against industry and location benchmarks
  • 401(k) retirement plan with company-matching
  • Employee Stock Ownership Plan (ESOP) - we're all company owners!
  • Flexible spending accounts
  • Employee assistance program (EAP)
  • Short- and long-term disability insurance
  • Life and accident insurance
  • Tuition assistance/Training/Workforce improvement reimbursement per year
  • Spot bonuses for exceptional performance
  • Annual Employee Recognition Awards with bonuses
  • Employee Referral Program
  • Free centralized, self-directed Learning Management System to learn at your own pace
  • Personalized career growth plans for every employee

Lynker is an E-Verify employer.
Lynker is an equal opportunity employer and makes all employment decisions based on merit, qualifications, and business needs. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other legally protected status under federal, state, or local laws.

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