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Python Notebook Jupyter Jobs (NOW HIRING)

Inficare Technologies

AI Specialist

Pontiac, MI · On-site

$80/hr

Python, R * ML Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn * Big Data & Analytics: Apache Spark, Databricks, Jupyter Notebooks * Cloud Platforms: AWS (SageMaker, EC2, S3), Azure (Machine ...

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How much do python notebook jupyter jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for python notebook jupyter in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What is a Python Notebook Jupyter?

Python Notebook Jupyter, commonly referred to as Jupyter Notebooks, are interactive web-based tools that allow users to write and execute Python code in a segmented, cell-based format. They are widely used for data analysis, machine learning, and visualization, providing an intuitive way to mix code, visualizations, and narrative text. Jupyter Notebooks are popular among researchers, data scientists, and educators for their flexibility and ease of sharing results. Additionally, they support multiple programming languages with the appropriate kernels, though Python is the most commonly used.

What are the key skills and qualifications needed to thrive as a Jupyter Notebook developer?

To thrive as a Jupyter Notebook Developer, you need strong proficiency in Python programming, data analysis, and a solid understanding of computational notebooks. Familiarity with Jupyter Notebook, data visualization libraries (such as Matplotlib, Seaborn), and tools like pandas and NumPy is typically required. Excellent communication, problem-solving skills, and attention to detail help convey complex ideas and collaborate effectively with team members. These skills enable efficient, reproducible, and collaborative data analysis workflows essential for research and data-driven decision-making.

How does a Python Notebook Jupyter developer typically collaborate with data scientists and other team members on projects?

As a Python Notebook Jupyter developer, collaboration with data scientists, analysts, and other stakeholders is a key aspect of the role. Developers often work in cross-functional teams, using Jupyter Notebooks to create, document, and share code, analyses, and visualizations in an interactive format. Effective communication is essential, as you may need to explain your code, help troubleshoot issues, or integrate feedback from peers. Version control tools like Git are commonly used to manage contributions and ensure smooth collaboration across the team.

What is the difference between Python Notebook Jupyter vs Data Analyst?

AspectPython Notebook JupyterData Analyst
CredentialsBasic programming knowledge, Python skillsDegree in statistics, data science, or related field
Work EnvironmentData science teams, research labs, tech companiesBusiness environments, consulting firms, finance, marketing
UsageData exploration, visualization, prototypingData cleaning, analysis, reporting

Python Notebook Jupyter is a tool primarily used for coding, data exploration, and visualization, often by data scientists and researchers. Data Analysts focus on interpreting data, creating reports, and supporting decision-making. While both roles work with data, Jupyter notebooks are a technical tool used by data analysts as well, but the roles differ in scope and focus.

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Python Notebook Jupyter jobs near you
Infographic showing various Python Notebook Jupyter job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 91% Full Time, 3% Part Time, and 5% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.

Data Scientist

Apogee Engineering, LLC

Colorado Springs, CO

$155K - $190K/yr

Full-time

Re-posted 27 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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