In this hourly, remote contractor role, you will work as a Pandas Specialist (SME) to create realistic, challenging computer-based tasks using Python Pandas and related data-analysis workflows. You will design practical Pandas tasks, document them clearly in SuperAnnotate, ensure your setup supports the task, and recor
About the role
In this hourly, remote contractor role, you will work as a Pandas Specialist (SME) to create realistic, challenging computer-based tasks using Python Pandas and related data-analysis workflows. You will design practical Pandas tasks, document them clearly in SuperAnnotate, ensure your setup supports the task, and record yourself executing the task on your computer.
Tasks may include loading datasets, cleaning data, filtering rows, grouping and aggregating data, merging datasets, handling missing values, reshaping data, exporting files, creating basic visualizations, or performing practical business/data-analysis workflows. Your work will help train advanced AI models to better understand how real users complete data manipulation and analysis tasks.
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 Pandas expertise directly helps improve the world’s premier AI models by teaching them how real users complete practical Python data-analysis workflows.
Create realistic Pandas tasks: Come up with realistic and challenging tasks that can be executed on the computer using Pandas, then document the task clearly in SuperAnnotate.
Prepare the work environment: Ensure your setup supports the task, including having Python/Pandas installed or available, datasets prepared, files accessible, and any required references ready before recording.
Record task execution: Record yourself executing the Pandas task on your computer while following project instructions and ensuring the workflow is clear, complete, and realistic.
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. …
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