Grading assessment in data science faces challenges related to scalability, consistency, and fairness. Synthetic dataset and GenAI enable us to simulate realistic code samples and automatically evaluate using rubric-driven systems. The research proposes an automatic grading system for generated Python code samples and explores GenAI grading reliability through human-AI comparison.