ZipRecruiter

Log In

3

Remote No Experience Data Science Jobs in Colorado

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 ...

Averna

Data Analyst

Denver, CO · Remote

Bachelor's degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics ... Advanced experience using analytics to solve engineering problems, performing statistical analysis ...

next page

Showing results 1-20

All JobsData Science JobsRemote No Experience Data Science JobsRemote No Experience Data Science Jobs in Colorado

Remote No Experience Data Science information

What is a remote no experience data science job?

A remote no experience data science job is an entry-level position that allows you to work from home or any location without requiring prior professional experience in the data science field. These roles typically focus on tasks like data cleaning, basic data analysis, or assisting senior team members with projects. Employers often seek candidates with foundational knowledge in programming languages like Python or R, basic statistics, and a willingness to learn. These jobs are ideal for recent graduates, career changers, or individuals who have completed relevant online courses or certifications.

What are common challenges faced by entry-level data scientists working remotely with no prior experience?

Entry-level data scientists working remotely often encounter challenges such as limited access to mentorship and real-time feedback, which can slow down the learning process. Additionally, remote roles may require strong self-discipline and proactive communication skills to collaborate effectively with team members across different locations and time zones. It's also common to face a steep learning curve when working with unfamiliar tools or large datasets, making it important to seek out online resources and actively participate in virtual team meetings. Building a professional network and asking questions regularly can help overcome these hurdles and accelerate growth in the field.

What are the key skills and qualifications needed to thrive as a remote no experience data scientist?

To thrive as a remote entry-level data scientist, you generally need foundational knowledge in statistics, data analysis, and programming (often in Python or R), which can be demonstrated through online courses or relevant degrees. Familiarity with tools like Jupyter Notebook, SQL, and data visualization platforms such as Tableau is beneficial, and certifications from platforms like Coursera or DataCamp can enhance your qualifications. Strong problem-solving abilities, effective communication, and self-motivation are crucial soft skills for collaborating remotely and interpreting complex data. These skills and qualities enable you to contribute meaningfully to data-driven projects, even without prior professional experience, and help you work efficiently in a remote environment.

Is it possible to get a data science job with no experience?

Entry-level data science positions often do not require prior professional experience if candidates have relevant skills such as programming in Python or R, knowledge of statistics, and familiarity with data analysis tools. Building a portfolio through online courses, projects, and certifications can improve chances of securing such roles without formal work experience.

What is the difference between Remote No Experience Data Science vs Remote No Experience Data Analyst?

AspectRemote No Experience Data ScienceRemote No Experience Data Analyst
Required CredentialsBasic understanding of data concepts, possibly some online coursesBasic Excel, data visualization, and analytical skills
Work EnvironmentRemote, collaborative with data science teamsRemote, often involved in reporting and data interpretation
Industry UsageUsed in tech, finance, healthcare for predictive modelingUsed across industries for reporting, trend analysis
Search & Comparison IntentPeople exploring entry-level data science roles without experienceIndividuals interested in entry-level data analysis roles

Remote No Experience Data Science and Remote No Experience Data Analyst roles share similarities in entry-level requirements and remote work settings. However, data science focuses more on predictive modeling and machine learning, while data analysis emphasizes reporting and data interpretation. Both roles are suitable for beginners with basic skills and are in high demand across various industries.

What job categories do people searching Remote No Experience Data Science jobs in Colorado look for? The top searched job categories for Remote No Experience Data Science jobs in Colorado are:
What cities in Colorado are hiring for Remote No Experience Data Science jobs? Cities in Colorado with the most Remote No Experience Data Science job openings:
Remote No Experience Data Science 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 7 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.

Apply