Pandas Data Analysis Task Creator

The work

You will create realistic computer-based tasks for AI training using Python, Pandas, CSV datasets, and Jupyter notebooks. The tasks should reflect practical data work in areas such as business, finance, operations, research, reporting, and analysis.

You will also check each task for completeness, clarity, realism, reproducibility, and compliance with project guidelines.

  • Create tasks for loading, cleaning, filtering, grouping, aggregating, merging, reshaping, analyzing, and exporting data.
  • Show practical workflows with Pandas DataFrames, Series, and common data-processing steps.
  • Review completed submissions and confirm that others can reproduce the workflow.

What it pays and takes

This is remote, hourly contractor work. The role is listed as entry level, but you need hands-on experience using Pandas in data cleaning, analysis, transformation, reporting, or data-processing workflows.

  • Pay: Up to $20 per hour.
  • Time: 20 or more hours per week.
  • Location: Candidates must be based in Bangladesh, India, or Pakistan.
  • Language: English proficiency at B2 level or higher.
  • Required: Strong knowledge of DataFrames, Series, indexing, filtering, sorting, grouping, merging, reshaping, missing values, and file input and output.
  • Required: Comfort running Python scripts or notebooks, managing files, installing packages when needed, and recording computer workflows.
  • Required: Strong attention to detail, self-direction, and reliable delivery.
  • Helpful experience: Python, statistics, finance, operations, reporting, research, or automation.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training uses human-created examples and reviews to help computer systems learn practical tasks, including data analysis and coding workflows. OpenTrain AI is the hiring and contracting organization for this role, giving contributors a way to build experience in this growing field.

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