The work
The partner title and supplied description name different subjects. Review the duties and qualifications before applying.
You will review AI-generated content about corporate finance and decide whether it reflects real financial workflows and professional practice. You will also produce structured outputs and written feedback that helps improve AI performance.
- Evaluate content about corporate finance, financial analysis, treasury, and enterprise finance operations.
- Use professional judgment to identify inaccurate or incomplete AI-generated responses.
- Complete analytical work and create structured data outputs using professional finance tools and workflows.
- Write clear, detailed feedback about issues in AI outputs.
- Work independently and asynchronously when active projects are available.
What it pays and takes
- Pay: Up to $80 per hour for qualifying project work.
- Work arrangement: Remote, part-time contract work with a flexible schedule.
- Time requirement: 20 or more hours per week.
- Location: Open to candidates in the United States.
- Language: Fluent written English.
- Experience: At least two years of professional experience in corporate finance, M&A, treasury, financial services, or an equivalent field.
- Relevant backgrounds include investment banking analysis, M&A analysis, corporate development analysis, treasury analysis or management, cash management, SAP FI/CO consulting, and S/4HANA finance analysis.
- Strong written communication, close attention to detail, sound professional judgment, and the ability to work independently are required.
- Experience with financial analysis, treasury management, enterprise finance systems, SAP FI/CO, S/4HANA Finance, M&A, corporate development, or cash management is useful.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site. OpenTrain is a platform where people find AI training and data-labeling work, create a profile, and start applications.
About AI training work
AI training work is the human side of building artificial intelligence. People review model responses, evaluate accuracy, and provide examples or feedback so AI systems can better handle professional topics such as finance.