Eliel Polanco

Data science graduate student with 15+ years of experience in insurance sales, claims, and business development. Skilled in Python, R, SQL, and Tableau with proven ability to analyze complex datasets, develop predictive models, and deliver actionable insights. Adept at bridging business expertise with advanced analytics to drive growth, optimize processes, and improve decision-making. Bilingual in English and Spanish.

Customer Segmentation using K-Means, Python, Tableau, Clustered customers by income, debt ratio, and auxiliary service use to create targeted marketing profiles. Built Tableau dashboards to visualize segments and drive business strategy. Predicting Stock Purchases, R, XGBoost, Logistic Regression, Developed classification models using stock fundamentals and macroeconomic indicators to forecast investor buying behavior. Achieved AUC = 0.82 with XGBoost. Mental Health Service Utilization Forecast, Python, Random Forest, LSTM, Integrated Google Trends search data with socioeconomic indicators to predict state-level demand for mental health services. Optimized models for RMSE 0.75.