Junior Data Analyst (Python)

New

PairedE-commerce data analysis

Location: ArgentinaFull-TimeJunior

Salary not disclosed

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Job Details

Have solid Python fundamentals, including files, lists, dictionaries, and data structures.
Have basic experience with pandas, including filtering, merging, and aggregation.
Apply strong attention to detail and a methodical approach to data validation.
Investigate data discrepancies and explain how conclusions were reached.
Write clearly in English for client-facing findings and reports.
Be comfortable using AI tools to support coding, analysis, and problem-solving.
Be willing to work with large and messy datasets.
Make careful decisions when data is incomplete or ambiguous.
Basic SQL knowledge is a nice to have.
Git/GitHub and pytest or another testing framework experience are nice to have.
Exposure to Amazon Vendor Central, chargebacks, deductions, or retail vendor operations is a nice to have.
Experience with Excel, CSV, or Parquet data at scale, or academic or personal Python/data analysis projects, is a nice to have.

Clean and normalize Excel, CSV, and Parquet datasets using Python and pandas.
Reconcile Amazon claims against invoices, purchase orders, and payment records.
Match inconsistent IDs while avoiding unsupported or ambiguous matches.
Classify discrepancies using defined recovery and reconciliation taxonomies.
Build pandas logic for underpayment checks, multi-currency analysis, and reversal matching.
Investigate unexpected results and trace discrepancies to their source data.
Write pytest or conformance tests to validate critical data-handling logic.
Determine when incomplete data is insufficient to support a recovery claim.
Process and analyze multi-million-row datasets across approximately 170 vendor accounts.
Generate accurate Excel, CSV, and PDF recovery reports for non-technical clients.

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