Quantitative Analyst - Fully Remote

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Data Science & Quantitative Analysis Expert
Type: Contract
Compensation: $60–$90/hour
Location: Remote
Commitment: 35 hours/week

Role Responsibilities

• Design complex analysis tasks simulating real research work, including data cleaning, statistical analysis, and interpretation.
• Author clear, reproducible reference analyses in Jupyter Notebooks or Google Colab.
• Build tasks for fair comparison between analytical approaches, backed by spot checks and recommendations.
• Evaluate how models handle tasks and verify the accuracy of their statistics and conclusions.
• Collaborate with researchers to ensure consistent and accurate evaluations.

Qualifications

Must-Have

• MSc or PhD in statistics, data science, or a quantitative STEM field, or equivalent experience.
• 1+ years in a research, research-engineering, or heavy data-analysis role.
• Proficiency in Python (pandas, NumPy) and Git.
• Strong data-analysis skills: data cleaning, statistical correlation, hypothesis testing, and result interpretation.
• Ability to communicate analytical findings effectively in writing.

Preferred

• Experience in AI training, model evaluation, or benchmark/task authoring.
• High attention to detail and creativity in task design.

Compensation & Legal

• Hourly contractor, Paid weekly via Stripe Connect

Application Process (Takes 20–30 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

• For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
• For any help or support, reach out to: [email protected]

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.