AI Tutor – Quantitative Finance Specialist

**1. Role Overview** Mercor is partnering with a leading AI research organization to engage professionals with advanced expertise in quantitative finance. This **full-time opportunity** invites quantitative traders, researchers, and financial engineers to help shape the next generation of AI models capable of reasoning about complex financial systems, strategies, and risk frameworks. As an **AI Tutor – Quantitative Finance Specialist**, you will play a pivotal role in advancing the organization’s mission to build AI that deeply understands markets, data, and human decision-making in finance. AI Tutors teach AI models how people think, analyze, and communicate within the world of quantitative finance. You will help develop financial reasoning, strategy evaluation, and market awareness through high-quality data contributions. This includes text, voice, and video-based work—such as labeling datasets, annotating market behaviors, or recording short explanations. Your expertise will ensure the model accurately captures how financial professionals reason through investment, trading, and risk challenges. This position is ideal for individuals who are analytical, precise, and passionate about both finance and technology. It requires curiosity, adaptability, and a commitment to innovation in a fast-moving environment. **2. Key Responsibilities** - Use proprietary tools to label, annotate, and evaluate AI-generated financial data - Contribute expert input across quantitative finance topics, including algorithmic trading, derivatives, and portfolio management - Collaborate with technical teams to refine data workflows and annotation systems - Analyze and critique AI-generated financial outputs to improve reasoning and accuracy - Create and evaluate challenging problems in financial modeling, backtesting, and quantitative analysis - Interpret evolving task instructions and apply sound professional judgment **3. Ideal Qualifications** - Master’s or PhD in Quantitative Finance, Financial Engineering, Financial Mathematics, Applied Mathematics, Statistics, or Economics with a quantitative focus - Proficiency in both formal and informal English communication - Strong research and analytical skills with experience using financial databases and resources (e.g., Bloomberg, Reuters, SEC filings) - Excellent organizational, interpersonal, and critical-thinking abilities - Independent problem-solver with attention to precision and detail - Passion for innovation and technology within quantitative finance **4. Preferred Background** - Professional experience as a quantitative trader, researcher, or analyst - Published work in reputable finance or economics journals - Familiarity with Python, R, or machine learning libraries (e.g., QuantLib) - Teaching or mentoring experience in finance, statistics, or applied mathematics - Professional certifications such as FRM, CQF, PRM, CAIA, or CFA **5. Work Environment** - Based in Palo Alto, CA (in-office, 5 days per week) or fully remote with strong self-management skills - U.S.-based applicants must reside outside of Wyoming and Illinois - Typical hours: 9:00am–5:30pm PST during training, then aligned with your local timezone - Remote workers must use a personal computer that meets one of the following requirements: a Chromebook, a Mac running macOS 11 or newer, or a Windows PC running Windows 10 or newer - Reliable smartphone access is required **6. Compensation & Benefits** - Competitive pay ranging from $90,000 to $200,000 annually for U.S.-based professionals, depending on experience and location - For international candidates, compensation ranges are available upon request - Access to medical benefits, subject to your country of residence - Supportive, high-impact environment focused on advancing AI and financial innovation **7. Application Process** - Submit your resume - Complete a 20-minute introductory interview - Selected candidates will move on to a focused quantitative finance data evaluation exercise - Finalists will participate in a team discussion and review of their expertise - The full process typically concludes within one week **8. About Mercor** Mercor is based in San Francisco, CA and specializes in recruiting experts for top AI labs. Our investors include Benchmark, General Catalyst, Peter Thiel, Adam D’Angelo, Larry Summers, and Jack Dorsey.