About this role Interview language: English 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 c
About the role
About this role
Interview language: English
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. 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.
Your profile
Hands-on experience using Jupyter Notebook or JupyterLab for Python, data analysis, visualization, teaching, research, automation, or documentation workflows.
English proficiency at B2 level or higher to understand project instructions, document tasks clearly, and communicate with the project team.
Comfortable using a computer, managing files, running notebooks, installing packages where needed, using browser/local environments, and recording workflows.
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.
Strong understanding of notebook basics such as code cells, markdown cells, execution order, kernels, imports, file paths, pandas, charts, outputs, and exports.
Ability to ensure your setup supports the task, including having Jupyter available, files/datasets prepared, packages installed, and any required references ready before recording.
High attention to detail when preparing the task, executing the workflow, and checking that the recording is complete and understandable. …
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