About the Role
Uber AI Solutions is inviting experienced domain professionals, specifically stock analysts, corporate finance professionals, and investment strategists, to collaborate on a new client project at the frontier of Generative AI (GenAI).
This is a freelance, paid, project-based opportunity designed for experienced professionals who want to apply their deep expertise in complex financial analysis and market dynamics to advance Generative AI systems.
What you’ll work on
- Your expertise will help train and evaluate the next generation of Generative AI systems.
- Collaborate with Generative AI researchers and engineers to translate high-level goals into detailed data collection and evaluation workflows.
- Execute and refine workflows independently, ensuring accuracy, consistency, and timely delivery.
- Conduct in-depth research to gather credible and up-to-date domain knowledge specific to financial markets, regulations, and reporting standards.
- Create original, high-quality content and complex research problems that challenge current AI model capabilities regarding financial forecasting, valuation, and market commentary.
- Fact-check and verify all content for precision and reliability, reducing the risk of misinformation related to financial data, calculations, and regulatory compliance.
- Provide expert feedback to enhance the performance, accuracy, and trustworthiness of Generative AI systems.
Project details
- Duration: Tasks for this project are expected to be available for 3 months (with potential extensions).
- Location: Remote (You must be based in the United States)
- Type: Freelance/Independent contractor
- Payout structure: Task-based pay model. Competitive rates per completed task, determined by the complexity and required experience.
- Schedule Flexibility: Hours are flexible and based on the applicant’s availability. Tasks are generally expected to be worked on during Mon-Fri business hours.
Who we are looking for
We are seeking individuals with deep, professional-level knowledge of stock markets, corporate finance, and investment analysis.
Financial Domain Expertise
- Current or former Equity Research Analysts, Sell-Side/Buy-Side Stock Analysts, Investment Analysts, or Portfolio Analysts who have produced client-facing stock reports, investment briefs, or market commentary for retail or mass-affluent audiences.
- Demonstrated expertise in company-level equity analysis, including valuation, earnings modeling, comparable-company analysis, catalyst identification, and risk assessment—specifically packaged in formats understandable to consumer clients (e.g., simplified narratives, actionable insights, clear buy/hold/sell rationales).
- Strong command of financial statements, valuation models, and capital markets dynamics, with the ability to translate complex concepts into high-clarity consumer-oriented research without sacrificing accuracy.
- Familiarity with regulatory and compliance expectations relevant to public-facing financial research (e.g., disclosures, conflicts of interest, SEC/FINRA communication rules for research distributed to non-institutional clients).
- Must be a practitioner-level financial professional—general financial awareness is not sufficient. Candidates should have held roles such as:
- Equity Research Analyst (sell-side or buy-side)
- Portfolio Analyst generating client reports
- Financial Journalist specializing in equities
- CFA or similar credentialed professional producing public-facing research
- Wealth Management Advisors
Core Professional Skills
- Proven ability to conduct deep research, identify credible primary and secondary financial sources, and fact-check meticulously.
- Expertise in content development, including designing original financial problems, scenarios, and evaluations in your field of specialization.
- Excellent writing proficiency, with a focus on precision, originality, and clarity in articulating complex financial concepts.
- Strong communication skills, with the ability to collaborate across teams and present complex information clearly.
AI Familiarity (A Plus)
- Familiarity with Generative AI concepts, prompt engineering, and data preparation is a plus.
- Awareness of ethical Generative AI practices, including bias detection and responsible data usage in the context of sensitive financial information.
Why this matters
By shaping the data and benchmarks these models rely on, you’ll help ensure that Generative AI is accurate, reliable, and aligned with the high ethical and factual standards of the financial industry. This is a unique opportunity to apply your domain knowledge at the cutting edge of technology.