AI Quant Tutor

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 organizations 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 worksuch 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

• Masters 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: 9:00am5:30pm 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 $90000 to $200000 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 DAngelo Larry Summers and Jack Dorsey.