AI Buy-Side Finance Tutor

Apply for the AI Buy-Side Finance Tutor (Full Time)role at Mercor . 1. Role Overview Mercor is partnering with a leading AI research organization to engage finance professionals with deep buy-side experience in a high-impact full-time project focused on training and refining next‐generation AI systems. As an AI Tutor – Buy‐Side Finance Data Specialist , you will leverage your expertise in portfolio management, hedge fund strategies, private equity investments, venture capital deal sourcing, and high‐frequency trading to enhance the accuracy and realism of advanced AI models. Using proprietary tools, you'll curate, annotate, and evaluate complex financial data to ensure models reflect the nuanced reasoning and decision‐making processes of real‐world buy‐side professionals. This opportunity is ideal for individuals with a strong analytical background, keen attention to detail, and a passion for driving innovation at the intersection of finance and AI. 2. Key Responsibilities Use proprietary software to label, annotate, and evaluate data across a range of buy‐side finance domains. Deliver curated, high‐quality data related to portfolio management, hedge fund strategies, private equity, venture capital, and algorithmic trading. Collaborate with technical teams to refine annotation tools and workflows. Identify and select complex financial scenarios that can meaningfully improve model performance. Interpret evolving task instructions with precision and sound judgment. Contribute to the development and evaluation of AI reasoning across investment and trading contexts. 3. Ideal Qualifications Professional experience in buy‐side finance or related roles (e.g., portfolio manager, hedge fund analyst, private equity associate, venture capitalist, or quant trader). Excellent analytical, organizational, and communication skills. Proficiency in written and spoken English, with the ability to interpret complex financial material. Strong attention to detail and ability to work independently. Demonstrated interest in the intersection of finance, data, and emerging technologies. 4. Preferred Qualifications Advanced finance certification such as CFA, CAIA, or equivalent. Experience mentoring, training, or leading teams in investment analysis or strategy. Comfort with recording short audio or video clips for model training. Familiarity with AI tools, data labeling, or annotation systems. 5. Work Environment & Requirements Full‐time position, available remotely or in‐person in Palo Alto, CA (5 days per week for on‐site). Initial training schedule: 9:00 a.m.–5:30 p.m. PST for two weeks; thereafter, work in your local time zone. Personal computer must be a Chromebook, Mac (macOS 11+), or Windows 10+ device. Reliable smartphone access required. U.S.-based applicants must reside outside of Wyoming and Illinois. Visa sponsorship not available. 6. Compensation & Terms $90,000–$200,000 per year for U.S.-based professionals, depending on experience and location. The posted range applies to U.S.-based candidates. For international applicants, Mercor's recruiting team will provide an estimated pay range specific to your location. 7. Application Process Submit your resume or CV to begin the process. Qualified applicants will complete a short initial interview (approximately 15 minutes). Selected candidates will proceed to a technical deep‐dive discussion and a brief take‐home evaluation. Final stage includes a virtual meeting with the broader team. The full interview process is designed to conclude within one week. 8. About Mercor Mercor connects top global talent with leading AI labs and research organizations, enabling experts across disciplines to contribute to frontier AI development. Our investors include Benchmark, General Catalyst, Adam D'Angelo, Larry Summers, and Jack Dorsey. Thousands of professionals in fields like law, finance, science, and engineering have joined Mercor to help shape the future of AI. Seniority level Not Applicable Employment type Full-time Job function Education and Training Industries Software Development #J-18808-Ljbffr