What You’ll Do

Create Prompt-Based Content

Create Responses to Coding Prompts

• Design coding exercises and sample responses to teach models how to generate a range of plots and graphs from structured prompts.
• Develop examples across data analysis scenarios involving basic statistics, distributions, and experimental methods.
• Ensure clarity, correctness, and completeness in both code and the associated visual outputs.

Assess Quality of Model Output

• Review responses generated by AI for correctness in code and visual presentation.
• Identify errors in statistical interpretation or visualization logic, and suggest improvements.
• Provide feedback on the model’s use of plotting libraries and its understanding of core data analysis workflows.

Support Evaluation Criteria

• Validate that visualizations convey appropriate insights based on statistical inputs like averages, variability, and distribution type.
• Check for proper usage of tools such as pandas, matplotlib, and seaborn, as well as structure and readability of code.
• Help refine evaluation guidelines by assessing performance across a range of prompt types.

We’re Looking For

• 7+ years of hands-on experience.
• Background in statistics or data science with applied experience in probability, hypothesis testing, and experimental analysis.
• Proficiency in Python, with strong skills in libraries such as pandas, matplotlib, seaborn
• Ability to interpret and evaluate code written for data visualization.
• Deep knowledge of statistical terms and techniques, including mean, median, standard deviation, and confidence intervals.

Nice to Have

• Exposure to libraries such as scikit-learn, SciPy, or statsmodels.
• Experience working with R or MATLAB in a data analysis or visualization context.

Understanding of basic experimental design (e.g. A/B testing) and its representation through visual data