Python + Pandas Developer Needed for Financial Data Processing

Project Description:

We are seeking a Python developer with strong Pandas expertise to build a script that processes financial data from multiple sources. The goal is to convert raw inputs into a structured Excel output with standardized transaction categories for reporting and analysis.

Data Sources (Input):

Bank statements (PDF and Excel formats)

Journal entries from an accounting system (Excel/CSV format)

Raw data exports from clients’ systems (various Excel/CSV formats)

Requirements:

Parse and consolidate data from all input sources

Classify transactions into categories, such as:

Sell / Purchase

Deposit

Interest

Gain & Loss

Withdraw

Output data into a clean, formatted Excel file (ready for reporting/reconciliation)

Code should be modular, well-documented, and easy to maintain

Handle variations in input file structures across clients/systems

Nice to Have:

Experience with OCR libraries (e.g., Tesseract, AWS Textract, etc.) for scanned PDFs

Background in accounting/finance data processing

Knowledge of Excel automation (formulas, pivot tables, or Power Query)

Deliverables:

Python script(s) using Pandas (and other relevant libraries)

Sample Excel outputs with transactions properly classified

Documentation / usage guide for running the scripts

Project Type:

One-time project with potential for follow-up work

Suitable for freelancers or small development teams

Budget:

Open to proposals — please provide a fixed-price or hourly rate and estimated timeline

How to Apply:

Please include:

Your relevant experience with Python, Pandas, and financial data

Any past projects involving bank statements, journal entries, or accounting data

Your proposed cost and timeline