Financial Quality Assurance Lead

About OpenTrain

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About AI Training Work

AI training is the human side of building artificial intelligence. Specialists review examples, evaluate model responses, and provide structured feedback so AI systems can produce more accurate, useful, and responsible results. In this role, your finance expertise will help improve how AI handles financial explanations and analysis.

• Work with AI-generated text and financial reasoning.
• Apply professional judgment to calculations, assumptions, and explanations.
• Help shape the quality of finance-focused AI systems.

The Financial Quality Assurance Lead Role

OpenTrain is hiring a Financial Quality Assurance Lead to review AI-generated finance content and trainer QA work across finance training projects. You will assess financial accuracy, analytical reasoning, calculation correctness, terminology, market and accounting awareness, risk sensitivity, clarity, formatting, instruction-following, and alignment with project rubrics.

You will also provide precise written feedback, communicate project updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. The role is designed for experienced finance reviewers who can contribute to quality operations across remote teams.

• Experience level: Intermediate
• Work arrangement: Remote contractor role
• Location: United States
• Availability: 20+ hours per week
• Compensation: Up to $90 per hour

What You'll Do

• Review AI-generated finance explanations, calculations, investment analyses, accounting interpretations, valuation workflows, risk discussions, market summaries, and problem-solving steps.
• Identify recurring quality issues and provide ongoing feedback to trainers and QAs.
• Communicate new guidelines, workflow updates, and quality expectations.
• Answer questions about financial reasoning, formulas, assumptions, accounting treatment, valuation logic, risk caveats, terminology, and rubric interpretation.
• Create and maintain style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Run onboarding and training calls and help improve scalable QA processes for finance AI training work.

Required Skills and Background

You should have a strong finance background and be comfortable evaluating detailed financial content against structured rubrics. The work requires careful review of calculations, assumptions, terminology, analytical logic, unsupported claims, and missing risk or accounting caveats.

Experience with AI training, data annotation, large language models, prompt or response evaluation, financial content QA, or rubric-based LLM evaluation is valuable. Professional certifications such as CFA, CPA, ACCA, FRM, CMA, CA, or an equivalent credential are a plus.

• Strong knowledge of financial statements, valuation, corporate finance, capital markets, investments, risk analysis, budgeting, forecasting, accounting principles, and time value of money.
• Ability to identify incorrect assumptions, flawed calculations, unsupported claims, and unclear explanations.
• Strong English communication skills for written feedback and team coordination.
• Experience with Excel or Google Sheets modeling, DCF, comparables, KPI dashboards, market research, financial databases, accounting systems, or financial reporting.
• Experience leading or supporting remote teams of trainers, reviewers, analysts, accountants, writers, researchers, educators, or QAs.
• High attention to detail and strong organization in remote, fast-moving workflows.

Education and Helpful Experience

A bachelor's or master's degree in Finance, Accounting, Economics, Business Administration, Financial Engineering, Quantitative Finance, or a closely related field is helpful. Relevant professional experience with finance workflows, documentation, remote review teams, or QA operations is also directly applicable.

• Finance, accounting, or related academic background
• Experience reviewing finance content or financial modeling work
• Background with remote review teams, documentation, or QA workflows
• Familiarity with AI training or LLM evaluation