Senior Data Scientist (Remote | $150–$200/hr)

Data Scientist

Position: Data Scientist

Type: Contractor

Compensation: $150–$200/hour

Location: Remote

About the Opportunity

We are seeking Data Scientists and Quantitative Professionals with experience at leading organizations to support an AI research project. You’ll evaluate AI model performance across statistics, machine learning, experimentation, and quantitative reasoning to help improve model accuracy and analytical capabilities.

Key Responsibilities

• Evaluate AI-generated outputs involving data science, statistics, machine learning, and quantitative problems.
• Create challenging prompts, datasets, and reference solutions.
• Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning.
• Assess data analysis, experimentation approaches, and data modeling techniques.
• Provide structured, actionable feedback to improve AI model performance.

Required Qualifications

• At least 1 year of experience at a leading company in technology, finance, research, or a related field, with some experience within the past 3 years.
• Strong understanding of Python, statistics, machine learning, and data analysis.
• Experience with Pandas, data modeling, and experimentation.
• Strong analytical and quantitative reasoning skills.
• Ability to communicate technical and statistical concepts clearly in writing.
• Based in an English-speaking country.

Preferred Qualifications

• Experience evaluating statistical models, machine learning outputs, or quantitative methods.
• Strong knowledge of experimental design, data interpretation, and methodological validation.
• Ability to develop rigorous datasets and reference solutions for complex analytical problems.

Compensation

• $150–$200/hour.
• Independent contractor engagement.
• Fully remote work.
• Approximately 100 openings available.

Application Process

1. Submit your application with relevant data science or quantitative experience.
2. Complete any required screening or technical evaluation.
3. Demonstrate your statistical reasoning and analytical skills.
4. Begin evaluating AI outputs and developing data science tasks if selected.