Collins Otieno

Achieved a 3.5 GPA in Computer Science with a focus on data analysis, utilizing Python, R, and SQL to build predictive machine learning models, design interactive Tableau dashboards, and engineer optimized data pipelines. This technical foundation is backed by multi-semester Dean’s List placements, a data analyst internship, a top-three finish in a data-focused hackathon, undergraduate research assistant experience, and a merit scholarship. Community contributions include leading the campus data science club, peer tutoring in statistics and database systems, competing in Kaggle data challenges, volunteering as a data mentor, and managing data pipeline automation for student organizations. To align this with your exact needs, are you aiming for a Data Analyst, Data Scientist, or Data Engineer position? If you want, tell me your preferred tech stack (like Pandas, Power BI, or AWS) so I can swap out the specific tools.