XGBoost

Data scientist with over two years of experience and a degree in Aeronautical Engineering, specializing in data engineering and data science projects. Expertise includes utilizing statistical analysis and machine learning methodologies to solve complex problems, with proficiency in tools such as Python, R, Power BI, and SQL. Recent accomplishments involve developing machine learning models for industrial applications, creating ETL tools for carbon emission reporting, and designing management dashboards to improve decision-making processes. Holds multiple certifications in Data Science and relevant technologies, demonstrating a commitment to continuous professional development.

Data scientist with over six years of experience specializing in artificial intelligence, machine learning, and statistical analysis across healthcare and industrial sectors. Demonstrated expertise in predictive modeling, time series forecasting, and causal inference, contributing to enhanced population health management and cost control within healthcare frameworks. Proven track record of developing advanced analytical solutions that yielded an 18% improvement in readmission predictions and a significant reduction in forecast inaccuracies through automated processes. Holds an academic background in Chemical Engineering and Complex Data Mining, complemented by certifications in cutting-edge tools such as Docker and PySpark. Proficient in utilizing machine learning frameworks and statistical methods to derive actionable insights and optimize operational efficiency. Multilingual with strong communication and stakeholder engagement skills, focused on driving innovation and delivering substantial results.