Mercor
[Hiring] AI Tutor – Quantitative Finance Specialist @Mercor
Mercor, Germantown, Ohio, United States
Oct 25, 2025 - Mercor is hiring a remote AI Tutor – Quantitative Finance Specialist.
Salary: $90,000 - $200,000 usd yearly. Location: USA.
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.
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
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: 9:00 am–5:30 pm 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
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
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
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.
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Salary: $90,000 - $200,000 usd yearly. Location: USA.
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.
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
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: 9:00 am–5:30 pm 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
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
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
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.
#J-18808-Ljbffr