Banking App PFM Data Annotator

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this remote AI training project. OpenTrain helps people build careers in AI training and data labeling, connecting contributors with flexible opportunities to improve the systems shaping modern technology.

Creating an OpenTrain account is free, and qualified contributors can apply in minutes.

About AI Training Work

AI financial advisors and other modern AI systems learn from examples prepared and reviewed by people. In this growing field, contributors classify conversations, evaluate responses, structure data, and review whether AI actions follow safe and useful patterns.

This work is remote and can offer a direct way to contribute to cutting-edge AI development while applying practical knowledge in finance, language, and data quality.

The Role

OpenTrain is seeking intermediate Banking App PFM Data Annotators to help prepare a financial conversation dataset for an AI financial advisor. You will label user requests, transaction and merchant categories, assistant responses, backend function calls, and SQL queries.

The project is worldwide and open to contractors working in Arabic and English. Compensation is a fixed price of $2,000 for the project.

• Work arrangement: Remote and worldwide
• Contract type: Contractor
• Experience level: Intermediate
• Languages: Arabic and English
• Data type: Text
• Payment: $2,000 fixed price

What You'll Do

You will turn financial conversation samples into structured records that can be used for model training and evaluation. Careful, consistent judgment will be important when identifying user intent, reviewing responses, and checking whether technical actions are appropriate.

• Classify intents such as spending insight, budgeting, and card support.
• Classify transactions and merchants by category.
• Label assistant responses for tone, completeness, and professionalism.
• Tag backend function calls, including get_user_summary, get_transactions, and run_custom_sql.
• Validate whether SQL queries are safe, parameterized, and read-only.
• Produce structured JSON records with the user query, labeled intent, function name when applicable, arguments, and assistant reply.

Requirements

This role is suited to contributors with practical personal finance knowledge and experience reviewing conversational or chatbot data. You should also be comfortable recognizing structured API-style actions and assessing basic SQL safety.

• Familiarity with personal finance terminology.
• Experience labeling chatbot or conversational data.
• Understanding of function calling and API-style structured data.
• Basic SQL literacy for identifying safe versus unsafe queries.
• Ability to work with Arabic and English text.
• Intermediate experience level.

Why This Project Matters

Every major AI system depends on human-reviewed examples. By labeling financial conversations and checking the quality and safety of AI actions, you will help shape how an AI financial advisor understands customer needs and responds to practical money questions.

OpenTrain contributors work at the human side of AI development, helping models become more accurate, useful, professional, and dependable.

How to Apply

Create a free OpenTrain account and submit your application for this Banking App PFM Data Annotator contract. Review the project details carefully and highlight your experience with personal finance, conversational data labeling, function calling, and basic SQL.

• Apply through OpenTrain.
• Use your Arabic and English language abilities in your profile.
• Emphasize relevant finance, chatbot annotation, API, and SQL experience.