Investment Banking & M&A - Finance Domain Expert | $100-$150/hr Remote
Overview
A senior finance expert will join a premier GenAI initiative to guide how financial knowledge is taught and evaluated in cutting edge AI models. You’ll shape instruction, define gold standards, and build benchmarks that measure true financial reasoning. This full-time, on-site role places you with a top AI lab through Cincinnatus LLC, blending deep domain insight with practical evaluation work.
What You'll Do4
- 1Assess the quality of finance related outputs and identify gaps in reasoning or flawed assumptions
- 2Create precise instruction specs and golden solutions that reflect real world financial tasks
- 3Develop challenging finance focused evaluation sets and benchmarks in collaboration with researchers
- 4Collaborate with specialists to standardize criteria and translate complex finance judgment into clear guidelines
Requirements5
- 15+ years of solid professional finance experience at a reputable institution such as investment banks, asset managers, PE or credit firms, or regulators
- 2Deep expertise in at least one core finance area like corporate finance and FP&A, M&A, asset management, private equity or credit, or risk management
- 3Evidence of senior individual contributor or leadership experience with ownership of analyses and decisions
- 4Advanced degree in finance, economics, accounting, or quantitative fields or relevant professional credentials (CFA, CPA, FRM)
- 5Practical experience with large language models in a professional setting and strong judgment between right and plausible but wrong answers
Who Should Apply
Ideal candidates are seasoned finance specialists who can operationalize finance knowledge for AI models. You thrive on turning tacit judgment into explicit criteria, enjoy cross disciplinary collaboration, and want a hands on role shaping how AI reasons about real finance tasks on-site in the Bay Area.
Salary Insight
Compensation ranges from $100 to $150 per hour.
Location
Required Skills
Application Tip
Share a concrete example of a finance project where you defined success metrics, wrote decision criteria, and evaluated model outputs to improve accuracy.
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