Mercury Electronics -
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TYPE OF WORK
Gig
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SALARY
$10USD / completed data dive
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HOURS PER WEEK
TBD
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DATE UPDATED
Mar 21, 2026
Job Type:
Project-Based / Part-Time (Recurring Research Projects)
Pay:
$10 USD per completed DataDive
Payments sent via PayPal after each approved batch
+$150 quality bonus after 100 DataDives (if clean and consistent)
Overview
We are looking for an experienced Amazon FBA product research specialist who is already very familiar with DataDive (Brandon Young method) and Jungle Scout and can begin work in the next 7 days without training.
This is not an entry-level VA role.
You must already know how to use these tools professionally.
Tools You MUST Already Know
DataDive (Brandon Young methodology, most important)
Jungle Scout (Catalyst & Product Database)
Google Sheets
If you need training on these tools, please do not apply.
Project Structure
Each project consists of 100 DataDives, completed in stages:
Trial Phase
First 5 DataDives
Then paid $50 with PayPal
Validation Phase
Next 20 DataDives
Reviewed
Then paid $200 via PayPal
Production Phase
Remaining DataDives completed in batches of 25
Each batch paid $250 via PayPal
After full completion of 100 DataDives, there may be no work for several months, then another project begins.
We expect to complete 400–500 DataDives over the next year.
Your Responsibilities
1. Product Discovery
Use Jungle Scout Catalyst and Product Database
Work within niches we specify
Apply correct price and revenue filters we specify
Identify strong product ideas for DataDive
2. DataDive Execution
Select at least 10 (15 is better) very similar competing products. If there are not 10 very similar competing products to select then a datadive can't be done for this niche.
Identify when niches should be split into multiple valid dives
(example: battery vs rechargeable versions)
Run separate DataDives when appropriate
3. Keyword Cleanup
Clean the Master Keyword List
Remove brand names
Remove irrelevant phrases
4. Keyword Expansion
Review Outliers and Residue keywords
Add relevant phrases when appropriate
5. Product Scorecard
Complete as much of the product scorecard in DataDive as possible
6. Google Sheet Reporting
For each DataDive, provide:
Link to the completed DataDive
Average variations per seller (found in Master Keyword List section)
Average price (found in Master Keyword List section)
Average listing age (found in Master Keyword List section)
Search volume percentage (found in Overview section)
Average rating (found in Master Keyword List section)
Important Notes
Payment is based on correct execution, not on finding “good” products
Some DataDives will be strong, many will not — this is expected
DataDives that are intentionally manipulated to improve metrics will not be accepted or paid
You must be able to work independently and follow the workflow accurately
How to Apply
Please include:
Your experience using DataDive and Jungle Scout
How long you have been doing Amazon product research
Confirmation that you are familiar with Brandon Young’s DataDive method
Any examples of past research work (optional)
Applications without real DataDive experience will not be considered.
