Grace

Research & Development Intern

Collected, cleaned and validated structured and unstructured datasets from multiple client sources using Python (pandas, NumPy) and SQL, ensuring data quality for downstream analytics.. Applied statistical methods (descriptive statistics, correlation analysis, outlier detection) to identify trends supporting evidence-based recommendations.. Assisted in prototyping interactive dashboards to visualize KPIs and operational metrics for stakeholder decision-making.. Developed Python scripts to automate repetitive data-extraction tasks, reducing manual processing time.. Documented data workflows and contributed to internal knowledge-sharing on BI best practices and the CRISP-DM methodology.