The Work
You will help improve AI systems that handle personal and consumer lending topics. The work combines response evaluation, rubric writing, and collaboration on training methods and benchmarks.
Your reviews will focus on whether model responses are accurate, clear, and sound from a consumer lending perspective.
- Evaluate AI responses about personal loans, auto finance, credit cards, student loans, and buy-now-pay-later products.
- Assess how responses handle credit scores, credit reports, affordability, APR, amortization, risk-based pricing, delinquencies, and charge-offs.
- Create clear rubrics for judging model accuracy and capabilities.
- Work with AI researchers and other lending experts on evaluation strategies, training methods, and benchmarks.
What It Pays And Takes
This is a fully remote freelance opportunity with a flexible part-time commitment. The initial project is expected to last about one month, with a possible extension based on project needs and performance.
- Pay: $100 per hour.
- Time commitment: 20+ hours per week.
- Location: Worldwide and fully remote.
- Experience level: Entry level.
- Experience: At least two years in personal or consumer lending, such as underwriting, credit risk analysis, loan origination, collections, loss mitigation, or lending product management.
- Knowledge: Consumer underwriting criteria, credit scoring models, loan pricing, and consumer protection requirements.
- Skills: Excellent written English, critical thinking, problem-solving, and the ability to explain lending judgments clearly.
- Helpful but not required: CFA, FRM, a credit risk certification, or an MBA in Finance.
- Prior AI experience is not required.
How It Works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI Training Work
AI training is the human work behind systems that generate and understand text. Contributors review model responses, explain what is correct or useful, and create standards that help AI improve; people with lending expertise are needed for finance-specific evaluations.