Amritha Devangana User

I’m a Data Science professional with a Master’s degree in Data Science and Analytics from the University of Leeds. I specialize in quantitative risk modeling and financial forecasting, combining time-series techniques with machine learning to extract signal from complex data.

In my recent role as Associate, Analytics & Reporting, I built and automated ETL workflows using Control-M and Linux shell scripting, improving pipeline efficiency by 40%. I also developed MIS reporting frameworks and dynamic data models that improved reporting efficiency by 30%.

I focus on data quality and statistical rigor—implementing validation and statistical auditing checks that reduced reporting errors by 25% across retail analytics datasets. I collaborate closely with stakeholders to translate requirements into data solutions, resolving 50+ monthly queries and maintaining 98% client satisfaction.

Through projects, I’ve applied ARIMA and GARCH for exchange-rate forecasting, built churn models using Random Forest and XGBoost, and developed a YOLO-based deep learning approach for skin disease (erythema) detection. I’m motivated by building models that are both measurable and practically useful.