AI Model QA & Data Analysis Specialist - Remote

prolificacademicltd; United States; Remote; USD 66,000 - 110,000; Full time

Job summary

prolificacademicltd is seeking data science and analytics professionals to apply expertise to paid tasks that train and assess AI models. After a short skills assessment, successful applicants may review model responses, verify analyses, and provide feedback on statistical reasoning.

Responsibilities include assessing AI-generated analyses for accuracy, running Python or R scripts, and describing strengths and weaknesses in data-driven insights.

Qualifications

• Bachelor’s, master’s, or doctoral degree in data science, statistics, mathematics, or a closely related quantitative discipline.
• Practical experience in data analysis, predictive modeling, or machine learning engineering.
• Strong statistical problem‑solving skills and the ability to interpret complex visualizations independently.
• Substantial experience using large language models in data workflows, with an understanding of their common errors.
• Clear communication of mathematical ideas and data findings; a PayPal account is needed to receive payment.

Responsibilities

• Assess AI-generated analyses and data insights for accuracy, clarity, and completeness.
• Verify statistical claims, formulas, and mathematical reasoning against reliable references.
• Run data scripts in Python or R to check results and edge cases.
• Describe model strengths and weaknesses in analysis, prediction, and statistical reasoning.
• Check that responses follow task guidelines and maintain appropriate technical standards.

Skills

Data analysis

Predictive modeling

Machine learning

Statistical reasoning

Python/R

Education

Bachelor’s/Master’s/PhD in data science or related quantitative field

Tools

Pandas

NumPy

scikit-learn

SQL

Tableau/Power BI/Matplotlib/Seaborn

Job description

prolificacademicltd is seeking data science and analytics professionals to apply expertise to paid tasks that train and assess AI models. After a short skills assessment, successful applicants may review model responses, verify analyses, and provide feedback on statistical reasoning.

Responsibilities include assessing AI-generated analyses for accuracy, running Python or R scripts, and describing strengths and weaknesses in data-driven insights.