Our client is seeking Python contractors to support an AI-enabled insurance data project. The role will focus on converting submission data-extraction logic into repeatable Python-based “recipes” for different treaty and transaction cases.

A recipe is a deterministic Python script designed to extract, transform and structure data from submission documents relating to a designated counterparty and transaction type.

The successful candidate will review business documents and AI-assisted extraction outputs, adapt existing Python logic, test extraction accuracy and support human-in-the-loop validation. This role is suitable for candidates with practical Python scripting experience, strong attention to detail and an interest in document processing, automation and insurance data.

1. Review submission documents and AI/coding-agent extraction outputs to identify required data points.
2. Read, understand and adapt existing Python recipe logic for additional treaty and transaction cases.
3. Create, test, replay and document assigned data-extraction recipes.
4. Extract and structure information from PDF, Excel, Word, email attachments, ZIP files, folders and other submission materials.
5. Verify extracted data against original source documents to ensure accuracy and traceability.
6. Record defects, missing data, source-file issues, extraction errors and logic gaps.
7. Support human-in-the-loop validation by identifying where each extracted value originated.
8. Work with project stakeholders to resolve data-quality and extraction issues.
9. Help improve the consistency and repeatability of the recipe-development process.
10. Use AI-assisted development or coding-agent tools where appropriate.
11. Prepare clear documentation so that recipe logic can be understood, maintained and replicated by other team members.

1. Basic to intermediate Python scripting capability.
2. Ability to read, understand and modify existing Python code.
3. Experience working with structured and unstructured files, including PDF, Excel, Word, email attachments, ZIP files and folders.
4. Ability to analyse business documents carefully and identify relevant data fields.
5. Good understanding of data validation, exception handling and reconciliation.
6. Strong attention to detail and accuracy.
7. Ability to document technical issues and extraction logic clearly and logically.
8. Good analytical, troubleshooting and problem-solving skills.
9. Willingness to learn reinsurance concepts, treaty structures and underwriting submission processes.
10. Good communication skills and ability to work effectively with project stakeholders.

1. Experience in the reinsurance or insurance industry.
2. Experience with data extraction, OCR, document parsing or automation workflows.
3. Experience using Python libraries for document and file processing, such as:
4. Pandas
5. OpenPyXL
6. PyPDF / PDFPlumber
7. Python-docx
8. Regular expressions
9. JSON and CSV processing
10. Experience in RPA, intelligent document processing or AI-assisted automation.
11. Exposure to insurance, banking, finance, actuarial, audit or consulting projects.
12. Experience validating extracted data against source documents and maintaining data lineage.
13. Familiarity with underwriting, treaty or policy-related documents would be an advantage.

The ideal candidate is a practical and detail-oriented Python developer who is comfortable working with complex business documents and adapting existing scripts to different file formats and transaction cases.

This role does not require advanced machine-learning model development. It is focused primarily on Python scripting, document extraction, data validation, testing and process repeatability.