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Data Science Manager Jobs in Colorado (NOW HIRING)

Environmental Data Scientist

Boulder, CO · On-site

$75K - $105K/yr

Lynker Corporation is a leading provider of innovative solutions in weather and climate science ... Free centralized, self-directed Learning Management System to learn at your own pace * Personalized ...

The data science team is at the forefront of driving business decisions; we are now scaling our ... This is not a pure people-management role. * Building, mentoring, and guiding a pragmatic, delivery ...

Data Processing: (Data management and curation, data description and visualization, workflow and ... science, and application specific knowledge. Through analytic modeling, statistical analysis ...

Demonstrate experience and knowledge of computer science concepts, data architecture, intelligence practices, and managing data in a big‑data environment. * Demonstrate expert knowledge of Python ...

Data Scientist

Colorado Springs, CO · On-site

$150K - $175K/yr

Support data management activities within large-scale, enterprise data environments. Required Qualifications * Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or ...

Demonstrate experience and knowledge of computer science concepts, data architecture, intelligence practices, and managing data in a big-data environment. * Demonstrate expert knowledge of Python ...

Data Scientist

Colorado Springs, CO · On-site

$150K - $175K/yr

Support data management activities within large-scale, enterprise data environments. Required Qualifications * Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or ...

Showing results 21-40

Data Science Manager information

See Colorado salary details

$32.6K

$102.1K

$180.9K

How much do data science manager jobs pay per year?

As of Aug 13, 2026, the average yearly pay for data science manager in Colorado is $102,149.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,400.00 and $132,000.00 per year, depending on experience, location, and employer.

What does a data science manager do?

As a Data Science Manager, your daily responsibilities typically include overseeing a team of data scientists and analysts, setting project priorities, and ensuring the timely delivery of data-driven solutions. You will often collaborate with cross-functional teams, such as engineering, product, and business stakeholders, to define problems, scope solutions, and communicate analytical insights. Your role also involves mentoring team members, reviewing code and analysis, and driving best practices in data science methodologies. This position requires balancing technical project oversight with team leadership and strategic business alignment.

What is a data science manager?

A Data Science Manager leads a team of data scientists to develop and implement data-driven solutions for business challenges. They oversee project timelines, ensure the quality of data analysis, and collaborate with cross-functional teams to drive decision-making. In addition to technical expertise, they require strong leadership, communication, and strategic thinking skills. Their role bridges the gap between data science initiatives and business objectives, ensuring the team's work aligns with company goals.

What is the role of a data science manager?

A data science manager oversees data science teams, guiding project priorities, setting strategic goals, and ensuring the effective use of data analysis and modeling techniques. They coordinate between technical staff and business stakeholders, often requiring skills in leadership, communication, and familiarity with tools like Python, R, or SQL. Their responsibilities include managing workflows, mentoring team members, and ensuring timely delivery of data-driven solutions.

What skills and qualifications are needed to be a data science manager?

To thrive as a Data Science Manager, you need strong analytical skills, experience in machine learning and data analytics, and a background in statistics or computer science, often supported by an advanced degree. Familiarity with tools like Python, R, SQL, cloud platforms, and experience managing data science projects are highly valued, and certifications such as Certified Analytics Professional (CAP) can be advantageous. Excellent leadership, project management, and communication skills are crucial for guiding teams and translating technical findings for stakeholders. These abilities ensure effective team performance, successful project delivery, and the alignment of data science initiatives with organizational goals.

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

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

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

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

What job categories do people searching Data Science Manager jobs in Colorado look for?

The top searched job categories for Data Science Manager jobs in Colorado are:

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

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

Infographic showing various Data Science Manager job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 13% Part Time, and 1% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $102,149 per year, or $49.1 per hour.

Environmental Data Scientist

Lynker Corporation

Boulder, CO • On-site

$75K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago


Job description

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.


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.

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.