Data Scientist (Masters) — AI Data Trainer About the Role What if your expertise in machine learning, statistical inference, and data engineering could directly shape how the world's most advanced AI systems reason about data?
Credit Analyst - Freelance AI Trainer
Job description
Please submit your CV in English and indicate your level of English proficiency.
Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.
What this opportunity involves
While each project involves unique tasks, contributors may:
- Evaluate AI-generated mortgage underwriting decisions across loan types (conforming, jumbo, FHA, VA, cash-out refinance);
- Create test cases involving qualifying income calculations for self-employed borrowers using Schedule C, K-1, and Schedule E;
- Draft and audit conditional approval letters and adverse action notices for Reg B / ECOA compliance;
- Distinguish Fannie Mae / Freddie Mac selling guide rules from lender overlays in jumbo and non-conforming loan scenarios;
- Document problem statements clearly and provide verified correct answers.
What we look for
This opportunity is a good fit for mortgage underwriters and loan origination professionals open to part-time, non-permanent projects. Ideally, contributors will have:
- Degree in Finance, Economics, Business Administration, Accounting, Real Estate, or any related field;
- 3+ years of of mortgage, lending, real estate, or financial services experience;
- Current or recent experience in underwriting & origination or adjacent roles;
- Ability to calculate qualifying income for self-employed borrowers from IRS Forms 1040, Schedule C, Schedule E, and K-1;
- Deep familiarity with Fannie Mae / Freddie Mac selling guides and knowledge of Reg B, Reg Z, and TRID disclosure timing rules;
- Strong written English (C1+).
How it works
Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid
Project time expectations
For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.
Compensation
On this project, contributors can earn up to $60 per hour equivalent, depending on their level and pace of contribution.
Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.
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