[Hiring] Data Science & Analysis - AI Training @Prolific Academic

Role Description

We’re looking for Data Scientists and Data Analysts to join our Expert Network to help train and evaluate cutting-edge AI models using real technical expertise. If you have the necessary experience, we’ll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you’ll be invited to join Prolific as a participant, where you’ll get paid to train and evaluate powerful AI models.

Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.

Qualifications

• Education: a BS, MS, or PhD in Data Science, Statistics, Mathematics, or a closely related quantitative field.
• Professional Experience: real-world experience in data analysis, predictive modeling, or machine learning engineering.
• Technical Rigor: the ability to solve complex statistical problems and interpret high-level data visualizations independently.
• Analytical Mindset: strong attention to detail with the ability to identify subtle logical fallacies in statistical reasoning or data interpretations.
• LLM Fluency: significant experience using LLMs to assist with data workflows, with a clear understanding of where these models typically hallucinate or fail.
• Communication: the ability to explain complex mathematical concepts or data insights clearly and concisely.
• A PayPal account to receive payment from our clients.

Requirements

• Evaluate LLM Responses: review AI-generated data insights and statistical analysis for accuracy, clarity, and completeness.
• Fact-Check Technical Claims: use authoritative references to validate mathematical proofs, statistical formulas, and data-driven conclusions.
• Validate Code & Outputs: execute data-related scripts (e.g., Python/R) to ensure they produce correct results and handle edge cases properly.
• Annotate Model Performance: identify strengths and weaknesses in how a model reasons through data problems or builds predictive models.
• Ensure Alignment: verify that model responses follow specific system guidelines and maintain a high standard of professional technical behavior.

Key Technologies

• Programming: proficiency in Python (Pandas, NumPy, Scikit-learn) or R.
• Data Querying: advanced SQL for complex data extraction and manipulation.
• Visualization: experience with tools like Tableau, PowerBI, or Matplotlib/Seaborn.
• Modeling: deep understanding of Machine Learning frameworks (PyTorch, TensorFlow) and statistical modeling techniques.

Benefits

• Chance to influence the AI models of the future using professional expertise.
• Competitive pay rates.
• Flexible hours.
• Ability to work from home.