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Python Data Scientist Jobs in Colorado (NOW HIRING)

ZR Sandbox

Data Scientist

Boulder, CO · On-site

$130K - $160K/yr

Analyze structured and unstructured data with Python and SQL.Build and validate predictive models.Communicate insights to stakeholders through reports and visualizations.Work with engineers to deploy ...

Hercules Industries

Data Scientist

Denver, CO · On-site

Hercules Industries is seeking a Data Scientist for a high-impact, strategic role responsible for ... as Python, R, SQL, and data visualization platforms • Strong problem-solving and analytical ...

CACI International, Inc.

Data Scientist - Mid

Denver, CO · On-site

$69K - $141K/yr

Work with modern Python-based tooling in an Agile, mission-focused delivery environment. * Grow your skills alongside senior data scientists, engineers, and mission stakeholders. Responsibilities:

Cymertek Corporation

Data Scientist

Aurora, CO · On-site

Cymertek Corporation is seeking a curious and innovative Data Scientist to join their team and help ... Required : • Bachelor's Degree • Proficiency in Python or R • Expertise in machine learning ...

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Python Data Scientist information

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$39.4K

$129.1K

$206.6K

How much do python data scientist jobs pay per year?

As of Aug 24, 2026, the average yearly pay for python data scientist 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 a Python data scientist?

A Python Data Scientist is a professional who uses Python programming language and its data analysis libraries to extract insights from large datasets. They apply statistical techniques, machine learning algorithms, and data visualization tools to solve business problems and make data-driven decisions. Python Data Scientists often work with tools like pandas, NumPy, scikit-learn, and Jupyter notebooks to manipulate data and build predictive models. Their role typically involves collecting, cleaning, analyzing, and interpreting complex data to help organizations make informed decisions.

What are some common challenges faced by Python data scientists when working with large datasets?

Python Data Scientists often encounter challenges related to processing and analyzing large datasets, such as memory limitations and slow computation times. To address these, professionals typically use libraries like Pandas, Dask, or PySpark to optimize data handling and leverage parallel computing. Collaborating closely with data engineers and IT teams can also help in setting up efficient data pipelines and scalable infrastructure. Staying updated with best practices in data preprocessing and model optimization is crucial for managing these challenges effectively.

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

To thrive as a Python Data Scientist, you need strong analytical skills, a solid understanding of statistics, machine learning, and proficiency in Python programming, typically backed by a degree in computer science or a related field. Familiarity with tools and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and version control systems like Git is essential. Problem-solving, curiosity, and effective communication are standout soft skills for this role. These abilities are crucial for extracting actionable insights from data, building predictive models, and collaborating across multidisciplinary teams.

What is the difference between Python Data Scientist vs Data Analyst?

AspectPython Data ScientistData Analyst
Required SkillsPython, machine learning, statistical analysis, data modelingExcel, SQL, basic statistics, data visualization
CertificationsData Science certifications, Python programming coursesData analysis or business intelligence certifications
Work EnvironmentData science teams, R&D, predictive modeling projectsBusiness units, reporting, data visualization tasks
Industry UsageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Python Data Scientists focus on building predictive models and advanced analytics using Python, while Data Analysts primarily interpret data through visualization and reporting. Both roles require strong analytical skills, but Python Data Scientists typically have more programming and machine learning expertise, making them suitable for complex data projects.

How much do Python data scientists make?

Python data scientists typically earn between $80,000 and $130,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and big data can command higher salaries, often exceeding $150,000. Compensation may also include bonuses and stock options in some companies.

Is Python good for data science?

Python is widely used by data scientists due to its simplicity, extensive libraries like Pandas, NumPy, and scikit-learn, and strong community support. It enables efficient data analysis, modeling, and visualization, making it a preferred programming language in the data science field.

What are popular job titles related to Python Data Scientist jobs in Colorado?

For Python Data Scientist jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Python Data Scientist jobs in Colorado look for?

The top searched job categories for Python Data Scientist jobs in Colorado are:

What cities in Colorado are hiring for Python Data Scientist jobs?

Cities in Colorado with the most Python Data Scientist job openings:

Python Data Scientist jobs near you
Infographic showing various Python Data Scientist job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $129,062 per year, or $62 per hour.

Data Scientist

Apogee Engineering, LLC

Colorado Springs, CO

$155K - $190K/yr

Full-time

Re-posted 16 days ago

Job description

Apogee is seeking a Data Scientist (DS) to support the U.S. Army Space and Missile Defense Command (USASMDC). This role applies data science, statistics, and automation to mission analytics, helping operational and intelligence teams process large, complex datasets and convert them into actionable insights in support of space and missile defense priorities.

The Data Scientist partners with analysts and technical stakeholders to identify high-value analytic problems, engineer and curate datasets, and develop reproducible pipelines and models to automate workflows and enrich mission data. Responsibilities include data exploration and feature engineering; building and evaluating statistical/ML approaches (as appropriate); developing scripts, tools, and dashboards to support analysis and reporting; and communicating results through clear documentation and briefings. The DS also supports data governance and quality efforts, ensures methods are transparent and repeatable, and transitions solutions into operational use in coordination with Government leads and mission users.

 

This is a full-time opportunity at Petterson Space Force Base (PSFB), CO.

****Contingent Upon Contract Award****


  • 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, and Jupyter Notebooks and/or Jupyter Labs.
  • Author cogent and logical scripts using Python and other applicable languages in a virtual environment using common Integrated Development Environments (IDE) such as VS Code, Spyder, PyScript, or Jupyter Notebooks.
  • Develop and use advanced software programs, algorithms, query techniques, models to solve complex intelligence problems, and automated processes to normalize, integrate, and evaluate data.
  • Debug existing and future Python code; refactor legacy code to ensure continued security, functionality, and compatibility.
  • Document and block-comment all code to ensure recoverability and error-checking, and enhance reading, checking, and maintaining code in accordance with common data science and coding standards, such as PEP-8 for Python,5 or using style-guide features embedded in common IDE applications, such as Spyder, VS Code, PyScript or others upon approval by the Government.
  • Collaborate across multi-discipline teams to ensure connectivity between various data sources and business problems.
  • Identify meaningful insights, interpret, and communicate findings, plus make recommendations to stakeholders.
  • Analyze requirements and evaluate technologies for data science capabilities including Natural Language Processing, Machine Learning, predictive modeling, statistical analysis, and hypothesis testing.
  • Maintain awareness of emerging analytics and big-data technologies.
  • Complete required course NSA NETA1400 (Technology Fundamentals for Analysis); recommended completion of any of the following NSA Courses: NETA2402/NETA2108 (Analysis II), RPTG2238, RPTG2235, RPTG3225, RPTG3222 (Basic Analytical Reporting) or equivalent curriculum.
  • Complete recommended certifications: Data Science Council of America (DASCA) certifications, such as Associate Big Data Engineer (ABDE), Associate Big Data Analyst (ABDA), and Senior Data Scientist (SDS); Google Data Analytics Professional Certificate; IBM Data Science Professional Certification.

Minimum Experience:

Citizenship: Must be a US citizen 
Clearance: Must have and be able to maintain a Top Secret (TS) with Sensitive Compartmented Information (SCI) adjudication
Education: Bachelors Degree
Years of Experience: 7+ years experience in data science/analytics engineering/software development in big-data environments.

Additional Experience:

  • Expert Python skills; heavy use of Jupyter Notebooks/Labs and common IDEs (e.g., VS Code/Spyder).
  • Proven ability to build and sustain automated data workflows (ingest/normalize/integrate/enrich/evaluate) using algorithms, queries, and models.
  • Strong SDLC skills: debugging, refactoring legacy code, and maintaining secure/compatible codebases.
  • Code quality discipline: clear documentation/block comments and adherence to PEP-8 (or equivalent style enforcement).
  • Working knowledge of data architecture and ability to collaborate across multi-discipline teams to connect data sources to mission problems.
  • Ability to communicate findings and recommendations to stakeholders.
  • Experience applying/evaluating ML/NLP, predictive modeling, and statistical methods (hypothesis testing).
  • NSA NETA1400 (Technology Fundamentals for Analysis) completion, or Government-approved equivalent.

Preferred Qualifications:
Additional Experience:

  • NSA courses: NETA2402/NETA2108 and/or RPTG2238/2235/3225/3222 (or equivalent).
  • Certifications: DASCA (ABDE/ABDA/SDS), Google Data Analytics, and/or IBM Data Science.
  • Experience transitioning prototypes into reusable, analyst-ready tools/pipelines and tracking emerging big-data/analytics tech.

Additional Information
Location: Petterson Space Force Base (PSFB), CO
On-site
Travel: 10%


USD $155,000.00 - USD $190,000.00 /Yr.

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