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Environmental Data Science Jobs in Colorado (NOW HIRING)

... in flexible environments that can scale as quickly as the market demands. Strategy and ... Essential Job Functions Data Science Strategy & Model Development * Develop predictive and ...

In this role, you will apply data science, statistical analysis, automation, and emerging technologies to complex operational challenges within the information environment and irregular warfare (IW ...

Data Scientist, NA

Denver, CO · On-site

$140 - $150/hr

... in flexible environments that can scale as quickly as the market demands.**Strategy and ... Data Science Strategy & Model Development*** Develop predictive and prescriptive models that ...

Oversee deployment and continuous monitoring of models in production environments to ensure optimal ... Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science ...

The data science intern will help drive proactive and predictive insights that inform strategic ... environment. Posted Date: 09/01/2026 This role will be posted for a minimum of 3 days. $20 min ...

New

The data science intern will help drive proactive and predictive insights that inform strategic ... environment. Posted Date: 09/01/2026 This role will be posted for a minimum of 3 days. $20 min ...

New

The data science intern will help drive proactive and predictive insights that inform strategic ... environment. Posted Date: 09/01/2026 This role will be posted for a minimum of 3 days. $20 min ...

New

The data science intern will help drive proactive and predictive insights that inform strategic ... environment. Posted Date: 09/01/2026 This role will be posted for a minimum of 3 days. $20 min ...

New

The data science intern will help drive proactive and predictive insights that inform strategic ... environment. Posted Date: 09/01/2026 This role will be posted for a minimum of 3 days. $20 min ...

New

Showing results 21-40

Environmental Data Science information

See Colorado salary details

$39.4K

$129.1K

$206.6K

How much do environmental data science jobs pay per year?

As of Sep 3, 2026, the average yearly pay for environmental data science in Colorado is $129,062.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,600.00 and $143,000.00 per year, depending on experience, location, and employer.

What is environmental data science?

Environmental Data Science is an interdisciplinary field that uses statistical, computational, and analytical techniques to collect, analyze, and interpret large sets of data related to the environment. Professionals in this field work on issues like climate change, pollution, biodiversity, and natural resource management by extracting meaningful insights from complex environmental datasets. Their work supports decision-making for policy, conservation, and sustainability initiatives. Environmental data scientists often collaborate with ecologists, geographers, and policymakers to address environmental challenges using data-driven approaches.

What are some common challenges faced by environmental data scientists when working with real-world datasets?

Environmental data scientists often encounter challenges such as incomplete or inconsistent data, varying data formats, and the need to integrate information from multiple sources like sensors, satellites, and field observations. Addressing missing values, data quality issues, and ensuring proper geospatial alignment can be time-consuming but is essential for producing reliable analyses. Collaboration with domain experts and stakeholders is frequently required to interpret findings and ensure that the results are actionable for environmental policy or management decisions.

What are the key skills and qualifications needed to thrive as an environmental data scientist, and why are they important?

To thrive as an Environmental Data Scientist, you need strong quantitative skills, expertise in environmental science, and a relevant degree in data science, statistics, or a related field. Familiarity with data analysis tools such as Python, R, GIS software, and experience with large datasets or machine learning techniques is typical. Exceptional problem-solving abilities, communication skills, and attention to detail set top performers apart in this field. These competencies are crucial for effectively interpreting complex environmental data, informing policy, and driving impactful sustainability initiatives.

What is the difference between Environmental Data Science vs Environmental Data Analyst?

AspectEnvironmental Data ScienceEnvironmental Data Analyst
Required CredentialsTypically requires a degree in data science, environmental science, or related fields; often includes programming and statistical certificationsUsually requires a degree in environmental science, geography, or related fields; may include basic data analysis certifications
Work EnvironmentResearch labs, data centers, environmental agencies, or consulting firmsEnvironmental agencies, research organizations, or consulting firms
Employer & Industry UsageUsed in environmental research, climate modeling, and policy analysisUsed in environmental monitoring, reporting, and data interpretation

Environmental Data Science focuses on developing models and algorithms to analyze complex environmental data, often requiring advanced programming skills. In contrast, Environmental Data Analysts primarily interpret and visualize environmental data to support decision-making. Both roles are vital but differ in technical depth and scope.

Is environmental data science a good major?

Environmental Data Science is a relevant major for careers involving analyzing environmental data, modeling ecological systems, and supporting sustainability efforts. It typically combines skills in data analysis, programming, and environmental science, preparing graduates for roles in research, consulting, or government agencies.

What does an environmental data scientist do?

An environmental data scientist analyzes environmental data to identify patterns, assess environmental risks, and support decision-making. They use statistical tools, programming languages like Python or R, and GIS software to interpret large datasets related to climate, pollution, and natural resources.

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

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

What are popular job titles related to Environmental Data Science jobs in Colorado?

For Environmental Data Science jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Environmental Data Science jobs?

Cities in Colorado with the most Environmental Data Science job openings:

Infographic showing various Environmental Data Science job openings in Colorado as of August 2026, with employment types broken down into 79% Full Time, 7% Part Time, 7% Temporary, and 7% Nights. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $129,062 per year, or $62 per hour.

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 27 days ago


Key responsibilities

  • Develop predictive and prescriptive models to support operational forecasting, capacity planning, energy optimization, and reliability analysis.

  • Integrate analytical models into operational workflows and identify opportunities for automation to streamline manual processes.

  • Partner with Data Engineering and Enterprise Architecture to ensure data pipelines support model accuracy, reliability, and alignment with long-term technology strategy.


Job description

About Vantage


Vantage powers, cools, protects and connects the technology of the world's well-known hyperscalers, cloud providers and large enterprises. Developing and operating across North America, EMEA and Asia Pacific, Vantage has evolved data center design in innovative ways to deliver dramatic gains in reliability, efficiency and sustainability in flexible environments that can scale as quickly as the market demands.

Strategy and Transformation

The Strategy and Transformation department is a dynamic and integral component of our business strategy, dedicated to enhancing our market position, business intelligence, and insights through data analysis.

Position Overview

This role will be based in Denver, CO. Following our flexible work policy (3 days in-office, 2 days flexible).

The Data Scientist plays a critical role in advancing Vantage's analytics, automation, and data-driven decision-making capabilities across North America. This role develops, operationalizes, and scales analytical models that improve forecasting accuracy, optimize data center performance, and enhance operational reliability across Vantage's rapidly expanding portfolio.

The Data Scientist partners closely with Operations, Engineering, Capacity Planning, Finance, Energy & Sustainability, and the Global Data Strategy team to transform raw operational data into actionable insights. This role designs and deploys predictive and prescriptive models that support capacity forecasting, energy optimization, anomaly detection, asset lifecycle management, and customer experience improvements.

Operating across regions and collaborating with global stakeholders, the Data Scientist ensures analytical models align with enterprise data architecture, governance standards, and long-term technology strategy. The role contributes to the evolution of Vantage's data platform, enabling scalable analytics capabilities that support growth, reduce operational friction, and strengthen decision quality across the business.

Essential Job Functions

Data Science Strategy & Model Development

  • Develop predictive and prescriptive models that support operational forecasting, capacity planning, energy optimization, and reliability analysis.

  • Identify high-value analytical opportunities across Operations, Engineering, and Customer Experience.

  • Build scalable machine learning pipelines that integrate with enterprise data platforms.

  • Evaluate model performance and implement continuous improvement mechanisms.

  • Result: High-impact analytical models that improve operational efficiency, reliability, and decision quality.

Workflow Integration & Automation

  • Integrate analytical models into operational workflows, including maintenance planning, incident response, and capacity forecasting.

  • Identify opportunities for automation and develop algorithms that streamline manual processes.

  • Result: Analytical capabilities embedded directly into operational workflows, improving speed, accuracy, and consistency.

Enterprise Data Alignment & System Integration

  • Define analytical requirements that inform data engineering, data quality, and data governance priorities.

  • Partner with Data Engineering to ensure data pipelines support model accuracy and reliability.

  • Collaborate with Enterprise Architecture to align analytical solutions with long-term technology strategy.

  • Support reduction of data silos and technical debt through disciplined data integration practices.

  • Result: A unified data ecosystem that enables scalable, reliable analytics across the enterprise.

Performance Measurement & Model Governance

  • Define KPIs and validation frameworks to measure model performance and business impact.

  • Ensure models adhere to governance standards, including version control, documentation, and reproducibility.

  • Partner with Operations leadership to ensure analytical outputs reflect real-world operational conditions.

  • Strengthen the linkage between model performance, operational reliability, and business outcomes.

  • Result: Analytical models that are trusted, transparent, and aligned with operational realities.

Additional Duties

  • Handle additional duties as assigned by management.

Job Requirements

  • Bachelor's degree in a quantitative discipline.

  • Master's degree preferred.

  • 5-8+ years of experience in data science, machine learning, and software engineering.

  • Experience with Full Stack AI assisted development and deployment.

  • Experience working with large-scale operational, IoT, or industrial datasets strongly preferred.

  • Background in predictive modeling, time-series forecasting, anomaly detection, and optimization algorithms.

  • Experience with Azure and Databricks.

  • Familiarity with data center operations, energy systems, or mission-critical environments preferred.

  • Experience collaborating with cross-functional teams in matrixed organizations.

  • Experience deploying models into production environments and integrating with enterprise systems.

  • Strong proficiency in Python, SQL, and machine learning frameworks (scikit-learn, TensorFlow, PyTorch).

  • Expertise in time-series modeling, statistical analysis, and data visualization.

  • Ability to translate complex analytical concepts into clear business language.

  • Strong understanding of data engineering principles and model lifecycle management.

  • Ability to work across Operations, Engineering, IT, and Data teams.

  • Strong communication, structured problem solving, and executive-ready storytelling.

  • Ability to balance analytical rigor with operational practicality.

  • Travel required is expected to be up to 20%, but may increase over time as business evolves

Physical Demands and Special Requirements

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the employee is occasionally required to stand; walk; sit; use hands to handle, or feel objects; reach with hands and arms; climb stairs; balance; stoop or kneel; talk and hear. The employee must occasionally lift and/or move up to 25 pounds.

Additional Details

  • Salary Range: $140,000 - $150,000 Base + Bonus (this range is based on Colorado market data and may vary in other locations)

  • This position is eligible for company benefits including but not limited to medical, dental, and vision coverage, life and AD&D, short and long-term disability coverage, paid time off, employee assistance, participation in a 401k program that includes company match, and many other additional voluntary benefits.

  • Compensation for the role will depend on a number of factors, including your qualifications, skills, competencies, and experience and may fall outside of the range shown.

We operate with No Ego and No Arrogance. We work to build each other up and support one another, appreciating each other's strengths and respecting each other's weaknesses. We find joy in our work and each other, actively seeking opportunities to inject fun into what we do. Our hard and efficient work is rewarded with an above market total compensation package. We offer a comprehensive suite of health and welfare, retirement, and paid leave benefits exceeding local expectations.


Throughout the year, the advantage of being part of the Vantage team is evident with an array of benefits, recognition, training and development, and the knowledge that your contribution adds value to the company and our community.


Don't meet all the requirements? Please still apply if you think you are the right person for the position. We are always keen to speak to people who connect with our mission and values.


Vantage is an Equal Opportunity Employer.

Vantage does not accept unsolicited resumes from search firm agencies. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of Vantage.


We'll be accepting applications for at least one week from the date this role is posted. If you're interested, we encourage you to apply soon-we're excited to find the right person and will keep the role open until we do!