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.

Product Manager at Say aam For All

September 1, 2025 - Present

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.

Data Science Intern at Dev Stack Solutions

November 1, 2021 - December 1, 2021

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.

Data Analyst Intern at Goal Street

May 1, 2020 - July 1, 2020

Extracted and transformed large datasets using SQL and Python (Pandas) to enable predictive analytics and trend monitoring for policy evaluation. Developed and optimized classification models (Decision Tree, Random Forest) in scikit-learn, achieving 83% accuracy in predicting visa/approval outcomes. Performed exploratory and statistical analyses to identify key drivers of approval rates, producing actionable insights and documentation.