Developed and integrated the GPQA Diamond Dataset for Graduate-Level Scientific Reasoning within the NVIDIA-NeMo/Gym repository, enabling multiple-choice question-based evaluation of advanced scientific reasoning. This work focused on dataset curation, seamless integration, and governance-friendly version control, ensuring commit-level traceability and compliance. Leveraging Python for data processing and API development, the contribution expanded the repository’s benchmarking capabilities and supported more rigorous, science-driven model evaluation. No major bugs were reported or fixed during this period, reflecting a focus on feature delivery and quality. The approach emphasized maintainable code, robust unit testing, and practices that enhance research credibility and reproducibility.