We are looking for a Financial and Investment Analysts to write, review, and validate prompt-based questions designed to train AI.
Your expertise in financial modeling, investment research, portfolio analysis, and market trends will ensure each prompt and response is analytically rigorous, compliant, and aligned with professional finance standards. We welcome professionals from asset management, equity research, investment banking, or corporate finance to help build AI training material that reflects how analysts evaluate risk, value assets, and make informed recommendations. You will also be required to write Python code to perform financial analysis.
You are a good fit if you:
Have Internship Experience as financial or investment analysts in organisations like a bank (Bank of America, JPMC, Morgan Stanley), hedge fund, private equity firm or asset/investment manager (Fidelity, Vanguard, State Street).
Have a bachelor's degree in finance, economics or a related field
Are currently based in the U.S., Canada, UK
Have a strong background in Python.
Demonstrate excellent verbal and written communication skills
Have strong attention to details
Preferred Qualification
Role Highlights
Flexible workload: 10–20 hours per week, with potential to increase to 40 hours.
Fully remote and asynchronous—work on your own schedule.
Minimum duration: 1–2 months, with potential for extension.
Role Start Date
Compensation and Legal Details
You will be legally classified as an hourly contractor for Mercor
We will pay you out at the end of each week via Stripe Connect
About Mercor
Mercor connects elite creative and technical talent with leading AI research labs, headquartered in San Francisco, CA. Our distinguished investors include Benchmark, General Catalyst, Peter Thiel, Adam D’Angelo, Larry Summers, and Jack Dorsey.
Apply today and redefine digital creativity alongside groundbreaking AI technologies!
We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.
Job ID: 2097
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