Data Analyst – Paid Finance Data Project (Remote)

Company: Human Data Labs
Job Type: Contract / Project-Based
Location: Remote – United States
Project Duration: Approximately 2 weeks

Payment: $250 USD per completed and approved dataset.

Referral Bonus: $50 USD for each referred participant who completes the project and has their dataset approved.

Human Data Labs is looking for US-based data analysts and other working professionals to participate in a short-term paid financial data project.

This is a project-based data opportunity, not a traditional Data Analyst position. We're looking for working professionals who regularly use multiple personal financial apps and services and can follow a structured data export and privacy workflow. review.

• Export data from financial apps and services you personally use.

• Provide data from at least 1 service in each of the 5 mandatory categories:

  • Banking & Neobanks

  • Credit Cards

  • Payments, P2P & Wallets

  • Credit Score & Identity

  • Tax Filing

• Provide exports from at least 2 additional eligible financial apps/services, bringing your submission to a minimum of 7 apps/services total.

• Submit 2 self-created financial artifacts, such as budget spreadsheets, tax workbooks, or net-worth/debt trackers.

• Use the provided PII-redaction tool to remove personal and banking identifiers on your own device before uploading your files.

• Follow project instructions to ensure your exports cover matching time periods and meet recency and quality requirements.

• Review and resubmit files if they are returned for rework during the quality review process.

• You must be 18 years of age or older.

• You must be a US resident.

• You must have a regular earning stream.

• You should be an experienced working professional.

• You must currently use financial services across all 5 mandatory categories.

• You must use at least 2 additional qualifying financial apps/services.

• You must be comfortable downloading and exporting data from your own accounts.

• You must be able to follow detailed instructions and data submission requirements.

• You should have strong attention to detail and be able to complete submissions accurately.

• You must be comfortable using a provided tool to redact personally identifiable information before submission.

• You must be able to complete the project within the required timeline.

Protecting your information is an important part of this project.

• PII redaction takes place on your own device.

• Raw exported files do not leave your device.

• Personal and banking identifiers are removed before files are uploaded.

• Account credentials and live financial data feeds are not collected.

• Submissions go through automated quality checks and a final human review.

• Data that does not receive Final Approval is not used and is deleted, with a Certificate of Destruction issued.

• Only approved, anonymized datasets are used for the licensed program in accordance with your consent.

To complete the project, your dataset must include:

• 1 eligible service from each of the 5 mandatory financial categories

• At least 2 additional eligible financial apps/services

• At least 7 apps/services total

• 2 self-created financial artifacts

• Recent, real financial data that meets the project's requirements

• Historical data covering the required project period

• Matching time periods across your financial app/service exports

• Successful completion of the project's quality checks and Final Approval

Strong participants follow the project instructions carefully, provide complete and accurate exports, properly redact their information before uploading, and respond promptly if any files need to be corrected or resubmitted.

Note for us internally: I'm deliberately keeping the historical-data bullet as “covering the required project period” for now. The source document says the newest transaction must be within 60 days, and history should be provided “as held,” typically 1–7 years, but it does not establish the 12-month vs. 2-year minimum you were discussing.