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AI Data Science Evaluator

Data Science - Remote Opportunity

About the Role

As an AI Data Science Evaluator, you will be crucial in refining AI's ability to interpret, analyze, and derive insights from data. Your work will involve assessing AI-generated data analysis, model performance, and statistical conclusions.

Your contributions will include:

  • Validating Data Insights: Reviewing AI-generated data analyses, reports, and predictions for accuracy, statistical soundness, and relevance.
  • Assessing Model Performance: Evaluating the output and performance metrics of AI/ML models, identifying potential biases or overfitting.
  • Annotating Complex Datasets: Labeling and categorizing intricate data points to improve AI's understanding of specific data types (e.g., time series, unstructured text, numerical data).
  • Refining Feature Engineering: Providing feedback on AI's ability to identify and create relevant features from raw data.
  • Troubleshooting AI Failures: Analyzing instances where AI models fail to perform as expected and offering insights for improvement.

Who We're Looking For

We're looking for individuals with a strong background in data science, statistics, or machine learning, and excellent analytical skills. Ideal candidates often possess:

  • Advanced coursework or a degree (Bachelor's or higher) in Data Science, Statistics, Computer Science, Machine Learning, or a related quantitative field from an accredited institution.
  • Familiarity with statistical concepts, data analysis techniques, and machine learning principles.
  • Experience with data manipulation tools (e.g., Python with Pandas/NumPy, R, SQL) is highly desirable.
  • Strong critical thinking to evaluate complex data narratives and model outputs.
  • Ability to explain data-driven insights clearly and concisely.

Compensation

Payment rates for core project work by data science experts typically range from 35 to 50 USD per hour in the US, reflecting the advanced technical skills required. Rates may vary based on your specialization (e.g., NLP, computer vision, time series analysis), depth of experience, and the complexity of the data science projects. Full payment terms will be provided for each project.