Finance Domain Expert — AI Training & Evaluation (Founding Cohort)

Company Description

Fana is an emerging AI company focused on building high-accuracy, domain-specific systems that help professionals make better, faster decisions. The team combines deep expertise in artificial intelligence, data, and product development to solve complex, real-world problems in finance. As part of a fast-moving, early-stage environment, team members collaborate closely, iterate quickly, and take ownership of meaningful work from day one. Fana values curiosity, rigor, and integrity, and seeks people who are excited to shape both its products and its culture. Joining Fana offers the opportunity to help define best practices for responsible AI in a critical industry.

Role Description

This is a part-time, remote role, for a Finance Domain Expert — AI Training & Evaluation (Founding Cohort). You will apply your finance knowledge to design, review, and refine prompts, scenarios, and datasets that train AI systems on real-world financial use cases. On a day-to-day basis, you will evaluate model outputs for accuracy and clarity, identify gaps or errors in financial reasoning, and provide detailed feedback that improves system performance. You will collaborate with machine learning engineers and product managers to translate complex financial concepts into structured tasks and evaluation criteria. The role also involves documenting standards, creating guidelines for financial correctness and compliance, and helping to define the quality bar for Fana’s finance-focused AI products.

Qualifications

• Strong finance domain expertise, with experience in areas such as corporate finance, investment analysis, financial modeling, or capital markets.
• Ability to interpret and analyze financial statements, reports, and datasets, and explain findings clearly to technical and non-technical stakeholders.
• Experience reviewing or creating structured financial documents (e.g., models, memos, credit analyses, investment theses, or research reports).
• Comfort working closely with data and AI systems, including evaluating outputs, identifying errors or biases, and proposing improvements.
• Excellent written communication skills, with the ability to articulate nuanced financial reasoning in precise, concise language.
• High attention to detail, strong critical thinking, and a disciplined approach to quality, documentation, and reproducible evaluation.
• Ability to thrive in an early-stage, collaborative environment, take ownership of projects, and adapt to evolving priorities.
• Bachelor’s degree in Finance, Economics, Accounting, or a related quantitative field; advanced degrees or professional certifications (e.g., CFA, CPA, MBA) are a plus.
• Experience in investment banking, asset management, private equity, equity research, corporate development, or related roles is strongly preferred.
• Interest in AI, data-driven products, and the future of technology

Compensation & Structure

• $100–$150 per accepted deliverable, depending on subdomain and complexity (most deliverables take 2–4 hours; effective rates are competitive with top expert networks)
• Paid trial tasks during onboarding — your time is compensated from day one
• 1099 contract; no minimum hours; flexible commitment of roughly 5–15 hours/week during active projects

Why Join the Founding Cohort

Priority access: founding experts are first in line for paid projects with frontier AI labs as we scale

Named credit: contribute to published benchmarks and evaluation reports under your own name

Ground floor: help define the quality standards, rubrics, and task designs that will shape how Fana works for years

Real impact: your expertise directly measures and improves what the world's most advanced AI systems can do

How to Apply

Apply with your resume or CV. Selected candidates will complete a short credential review and two paid trial tasks. We review applications on a rolling basis and the founding cohort is intentionally small. Early applicants have the best odds.

Fana is an equal opportunity employer. We evaluate applicants solely on expertise and quality of work, without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status.