Loka Adarsh Dronamraju

Analyzed large-scale datasets using structured analytical frameworks to assess data quality, consistency, and relevance. Applied data quality validation techniques and pattern analysis to identify inconsistencies across outputs and improve downstream analytical reliability.

Collaborated with cross-functional stakeholders (design, engineering, and project management) to translate user needs into actionable product requirements. Maintained product documentation on the product wiki and incorporated user feedback to inform feature prioritization. Defined concise PRDs, user flows, and acceptance criteria for web app features.

Developed data pipelines in Python (Pandas, NumPy) to clean and transform 9.8K+ grocery and sales records, ensuring accuracy and scalability for analytical modeling. Built time-series forecasting (ARIMA, Holt-Winters) and clustering models (K-Means, PCA) to predict monthly sales and categorize 48+ items into 14 optimized categories, improving forecast accuracy by ~15%. Validated and visualized model performance using logistic regression, evaluating classification performance and trends; presented actionable insights to leadership.