About Me
I am a Data Scientist with experience in the telecommunications industry, specializing in predictive modeling, clustering, and customer segmentation. Currently, I work on developing machine learning models to optimize financial scoring, churn prediction, and user engagement strategies within digital platforms.
My expertise includes working with Python scikit learn, LightGBM, Spark ML, SQL Hive, Teradata, and visualization tools like Power BI and Zeppelin. One of my most impactful projects was building a commercial propensity model that helped identify high value prepaid customers who behave like postpaid users, improving campaign targeting.
I enjoy tackling complex data challenges, optimizing model performance, and ensuring business decisions are backed by solid analytics. I am excited about this opportunity because it aligns with my passion for leveraging data driven insights to enhance business strategies and customer experiences.
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