Full-Time AI Tutor - Quantitative Finance Specialist

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.

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.

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

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

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

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