Data Scientist
Scrinium Digital
Mar 2023 — Jun 2026Built demand and sales prediction models and automated data pipelines; reported 18% higher model accuracy and 35% faster dataset preparation.
• Engineered and deployed supervised machine learning models to predict demand patterns and sales trends across 1M+ transactional records, improving model accuracy by 18%. • Architected automated data preprocessing and feature engineering pipelines in Python (Pandas, NumPy), cutting dataset preparation runtime by 35% and enhancing feature quality. • Executed comprehensive exploratory data analysis (EDA) using Matplotlib and Seaborn to identify critical predictive variables and guide model design decisions.
