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Remote Jupyter Notebook Jobs (NOW HIRING)

GCP DevOps Engineer

$54 - $74/hr

Remote 12+ Months Project Client : VZ * Experience in building pipelines, I/CD Continuous ... Extensively worked with Dataproc, GCS, Dataflow, GKE, Bigquery, Jupyterlab, Jupyter notebook ...

Jupyter Notebook-based data engineering and geospatial data layer creation * Metadata tagging, data ... Host remote training materials, provide access to self-paced learning modules, and facilitate ...

Jupyter Notebook-based data engineering and geospatial data layer creation * Metadata tagging, data ... Host remote training materials, provide access to self-paced learning modules, and facilitate ...

Jupyter Notebook-based data engineering and geospatial data layer creation * Metadata tagging, data ... Host remote training materials, provide access to self-paced learning modules, and facilitate ...

Python Developer

$51.50 - $71/hr

Python Developer Mountain View, CA (Remote) Interview Process: 2 rounds will be Zoom Video Primary ... Conda • Experience using Jupyter notebooks for e.g. Data science or ML tasks • Manage ...

Draper, UT (Remote work accepted from anywhere in US) Note: Look for architect level resources who ... Python, Pandas, Jupyter notebooks What We're Looking For * 10+ years of extensive professional ...

... Jupyter notebooks, or scientific visualization. • Experience leading or supporting remote teams ... of researchers, educators, reviewers, annotators, science writers, or QAs. • Experience with AI ...

Remote, U.S. must live near a target federal customer hub: Washington, DC metro (NGA, NRO, Pentagon ... Comfortable with Python and at least one frontend or notebook stack (Streamlit, Next.js, Jupyter ...

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Remote Jupyter Notebook information

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How much do remote jupyter notebook jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for remote jupyter notebook in the United States is $40.23, according to ZipRecruiter salary data. Most workers in this role earn between $31.73 and $46.39 per hour, depending on experience, location, and employer.

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

AspectRemote Jupyter NotebookData Analyst
Required credentialsKnowledge of Python, data visualization, and basic data analysisBachelor's in statistics, mathematics, or related field; often some programming knowledge
Work environmentPrimarily online, flexible location, often independentOffice or remote, collaborative teams, client-facing or internal projects
Industry usageUsed for data analysis, machine learning, and research tasksUsed for interpreting data, creating reports, and supporting decision-making

Remote Jupyter Notebook professionals focus on coding, data manipulation, and analysis using Python in a flexible environment. Data Analysts interpret data, create reports, and support business decisions, often with similar technical skills but a broader focus on communication and reporting. Both roles may overlap in skills but differ in scope and daily tasks.

What are the key skills and qualifications needed to thrive as a Remote Jupyter Notebook Developer, and why are they important?

To thrive as a Remote Jupyter Notebook Developer, you need strong programming skills in Python, experience with data analysis, and a solid understanding of computational notebooks and version control, often supported by a degree in computer science or a related field. Familiarity with JupyterLab, Git, virtual environments, and data visualization libraries like pandas, matplotlib, or seaborn is typically required. Excellent problem-solving, communication, and self-management skills help you collaborate effectively and deliver results independently in a remote environment. These skills are essential for producing high-quality, reproducible code, effectively sharing insights, and maintaining productivity without in-person supervision.

What is a Remote Jupyter Notebook?

A Remote Jupyter Notebook is an interactive computing environment that runs on a server rather than your local computer, allowing users to create and share documents containing live code, equations, visualizations, and narrative text from anywhere with internet access. This setup is especially useful for collaboration, leveraging greater computing resources, or working securely with sensitive data. Users connect to the remote server via a web browser, making it possible to utilize powerful cloud-based or institutional hardware without needing to install complex software locally.

What are some common challenges faced by professionals working with Remote Jupyter Notebook environments, and how can they be addressed?

Professionals working with Remote Jupyter Notebooks often encounter challenges such as managing dependencies across remote servers, ensuring the security of sensitive data, and maintaining stable network connections. Addressing these issues typically involves using containerization tools like Docker to standardize environments, implementing strong authentication and encryption protocols, and leveraging cloud-based platforms that provide reliable access and backups. Collaborating with IT and DevOps teams can also help streamline setup and troubleshooting, making remote work more efficient and secure.
More about Remote Jupyter Notebook jobs
What cities are hiring for Remote Jupyter Notebook jobs? Cities with the most Remote Jupyter Notebook job openings:
What are the most commonly searched types of Jupyter Notebook jobs? The most popular types of Jupyter Notebook jobs are:
What states have the most Remote Jupyter Notebook jobs? States with the most job openings for Remote Jupyter Notebook jobs include:
Infographic showing various Remote Jupyter Notebook job openings in the United States as of June 2026, with employment types broken down into 100% Part Time. Highlights an 37% Physical, 3% Hybrid, and 60% Remote job distribution, with an average salary of $83,671 per year, or $40.2 per hour.
GCP DevOps Engineer

$54 - $74/hr

Full-time

Posted 16 days ago


Job description

Job Title:GCP DevOps Engineer
Location : Remote
12+ Months Project
Client : VZ
  • Experience in building pipelines, I/CD Continuous Integration and Continuous Delivery.
  • Experience in Build automation tools like Jenkins, Docker, Kubernetes.
  • Expert in using different source code version control tools like Git.
  • Installation, configured of DNS, Load Balancer, SSL, HTTP, FTP and TCP/IP.
  • Experience with Containers and orchestration services like Kubernetes, Docker etc.
  • Experience in Public Cloud Architecture and Engineering in Google Cloud Platform (GCP)
  • Experience in configuration, deployment, management, and maintenance of large cloud-hosted systems,scaling, monitoring, performance tuning, troubleshooting and disaster recovery
  • Experience with Linux/UNIX environments and scripting for Build & Release automation.
  • Application Deployments & Environment configuration using Terraform, Ansible.
  • Involved in installing, configuring, and administering Hadoop clusters.
  • Hadoop Administration, Spark tuning, Data rebalancing and Tuning Map reduce, Spark Jobs.
  • Extensively worked with Dataproc, GCS, Dataflow, GKE, Bigquery, Jupyterlab, Jupyter notebook, Vertex-ai and Domino .