I am a Data Scientist with 3+ years of cross-industry experience, specializing in predictive analytics and machine learning solutions that drive operational efficiency and revenue growth. I translate unstructured data into actionable insights using NLP and deep learning, bridging technical rigor with stakeholder needs through clear visualizations. I work with Python and SQL to develop end-to-end ML solutions that deliver measurable business impact.
Highlights from my recent roles include building an XGBoost-based ETA prediction model at Blusmart that reduced trip delays by 20%, decreased delay-related cancellations by 10%, and cut driver penalty complaints by 12%. I also contributed to US Consumer Credit Risk modeling at American Express, improving identification of high-risk defaulters and enabling substantial loss reduction, while automating UAT/PIV testing and monitoring workflows. I enjoy collaborating with cross-functional teams and presenting results to leadership.
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