Remote Finance Specialist - AI Model Evaluation (Contract)

Mercor; San Francisco (CA); Remote; USD 90,000 - 124,000; Part time

Job summary

Mercor is hiring a Finance Specialist for a contract role with remote work in the United States. The position requires 8+ years of professional finance experience at top-tier firms and hands-on evaluation of AI model outputs using structured rubrics.

Responsibilities include guiding finance-related tasks, creating robust evaluation tasks, and collaborating with SME teams to ensure accurate training data. The role demands strong communication and ongoing weekday availability for 35 hours per week.

Qualifications

• Must have 8+ years of dedicated finance experience at a top-tier organization (e.g., Goldman Sachs, JPMorgan, Morgan Stanley, BlackRock, Fidelity, Deloitte, PwC, EY, KPMG).
• Experience evaluating LLM/AI model outputs against rubrics or scoring criteria.
• Demonstrated career progression expectations (Analyst → Associate → VP/Director).
• Ability to reliably engage for at least 35 hours/week on weekdays.

Responsibilities

• Guide research and engineering teams to close knowledge gaps in financial reasoning, analysis, and decision-making.
• Design finance tasks and write accurate, well-reasoned solutions grounded in real financial practice.
• Evaluate AI model outputs against rubrics and provide clear feedback on correctness and reasoning quality.
• Develop and refine evaluation guidelines and scoring rubrics for finance tasks.
• Collaborate with subject matter experts to ensure consistency and accuracy in training data.

Skills

Finance experience

AI model evaluation

Career progression

Communication skills

Job description

Mercor is hiring a Finance Specialist for a contract role with remote work in the United States. The position requires 8+ years of professional finance experience at top-tier firms and hands-on evaluation of AI model outputs using structured rubrics.

Responsibilities include guiding finance-related tasks, creating robust evaluation tasks, and collaborating with SME teams to ensure accurate training data. The role demands strong communication and ongoing weekday availability for 35 hours per week.