{"html":"<p>In this hourly, remote contractor role, you will work as a Jupyter Notebook Specialist (SME) to create realistic, challenging computer-based tasks using Jupyter Notebook, JupyterLab, or notebook-based data workflows. You will design practical notebook tasks, document them clearly in SuperAnnotate, ensure your setup supports the task, and record yourself executing the task on your computer.</p>\n<p>Tasks may include creating notebooks, running Python cells, data cleaning, exploratory analysis, visualization, markdown explanations, package imports, debugging, CSV/Excel handling, simple machine learning workflows, or reproducible data-science demonstrations. Your work will help train advanced AI models to better understand how real users complete notebook-based coding and data-analysis workflows.</p>\n<p>This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Jupyter Notebook expertise directly helps improve the world’s premier AI models by teaching them how real users complete practical data, coding, analysis, and documentation workflows.</p>\n<h3>Responsibilities</h3><ul><li>Create realistic Jupyter Notebook tasks: Come up with realistic and challenging tasks that can be executed on the computer using Jupyter Notebook or JupyterLab, then document the task clearly in SuperAnnotate.</li><li>Prepare the work environment: Ensure your setup supports the task, including having Jupyter available, datasets prepared, packages installed, notebooks created, and any required references ready before recording.</li><li>Record task execution: Record yourself executing the Jupyter Notebook task on your computer while following project instructions and ensuring the workflow is clear, complete, and realistic.</li><li>Document task context: Provide enough task context, steps, goals, files, dataset details, and notes so reviewers can understand what the task is and how it was completed.</li><li>Demonstrate practical software use: Complete workflows involving Python cells, markdown explanations, data cleaning, pandas, charts, debugging, imports, file handling, notebook outputs, or exports where relevant.</li><li>Maintain submission quality: Review your recording and documentation before submission to ensure the task is complete, reproducible, understandable, realistic, and aligned with project guidelines.</li></ul><h3>Requirements</h3><ul><li>Hands-on experience using Jupyter Notebook or JupyterLab for Python, data analysis, visualization, teaching, research, automation, or documentation workflows.</li><li>English proficiency at B2 level or higher to understand project instructions, document tasks clearly, and communicate with the project team.</li><li>Comfortable using a computer, managing files, running notebooks, installing packages where needed, using browser/local environments, and recording workflows.</li><li>Ability to come up with realistic and challenging Jupyter Notebook tasks that reflect actual data analysis, coding, education, research, reporting, or technical documentation use cases.</li><li>Strong understanding of notebook basics such as code cells, markdown cells, execution order, kernels, imports, file paths, pandas, charts, outputs, and exports.</li><li>Ability to ensure your setup supports the task, including having Jupyter available, files/datasets prepared, packages installed, and any required references ready before recording.</li><li>High attention to detail when preparing the task, executing the workflow, and checking that the recording is complete and understandable.</li><li>Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones.</li><li>Additional professional skills are appreciated, including Python, data analysis, machine learning, statistics, research, teaching, coding, reporting, or other computer-based workflows.</li></ul>"}