Remote Data Scientist for AI Model Evaluation

prolificacademicltd; United States; Remote; USD 91,000 - 129,000; Full time

Benefits offered by this job

Remote work

Flexible hours

Job summary

Prolific Academic Ltd seeks data science and analytics experts to work on paid tasks that train and assess AI models. After a short skills assessment, you may be invited to review model responses and provide feedback on how systems reason through data problems.

Responsibilities include verifying statistical claims, running Python or R scripts, and describing model strengths and weaknesses in analysis and statistical reasoning. Remote, flexible hours.

Qualifications

• Degree in a quantitative field with strong analytics background.
• Experience in data analysis, predictive modeling, or ML engineering.
• Ability to interpret complex visualizations independently.
• Attention to detail and detection of flawed statistical reasoning.
• Familiarity with large language models in data workflows.

Responsibilities

• Assess AI-generated analyses for accuracy and completeness.
• Verify statistical claims and formulas against references.
• Run Python or R scripts to check results and edge cases.
• Describe model strengths and weaknesses in analysis and reasoning.
• Ensure responses follow task guidelines and technical standards.

Skills

Data analysis

Predictive modeling

Machine learning

Statistical reasoning

Visualization interpretation

Attention to detail

LLM workflows

Communication of findings

Education

Bachelor’s degree in data science

Master’s degree in data science/statistics/math

Doctoral degree in quantitative field

Tools

Python

Pandas

NumPy

scikit-learn

SQL

Tableau/Power BI

Matplotlib/Seaborn

PyTorch/TensorFlow

Job description

Prolific Academic Ltd seeks data science and analytics experts to work on paid tasks that train and assess AI models. After a short skills assessment, you may be invited to review model responses and provide feedback on how systems reason through data problems.

Responsibilities include verifying statistical claims, running Python or R scripts, and describing model strengths and weaknesses in analysis and statistical reasoning. Remote, flexible hours.