Calvin Kreusser

Experienced Data Scientist and serverless full-stack engineer with a 2.5-year track record at Lockheed Martin, specializing in AWS utilization. Adept in front and back-end development, excelling as both a team member and lead. Enthusiastic lifelong learner, known for tackling challenging tasks with a positive attitude. Holds a Master of Science – Data Science degree from the University of Denver.

BINOMIAL DISTRIBUTION ANALYSIS

• Conducted Binomial Distribution Analysis on Wisconsin Breast Cancer (Diagnostic) Dataset, focusing on key features.
• Enhanced efficiency through Principal Component Analysis (PCA) dimensionality reduction.
• Developed six classifiers; Logistic Regression excelled with 0.982 accuracy and strong malignant case recall.

• Explored bike-sharing dataset, unveiling peak hours, seasonal trends, and weather impact.
• Modeled regressions (Decision Tree, Random Forest, Bagging) with R-squared surpassing 0.999.
• Optimized Random Forest through techniques like Randomized Search CV for robust demand prediction.

• Predicted income using Logistic Regression, Decision Trees, Naïve Bayes, and Random Forests.
• Applied PCA for dimensionality reduction and K-means clustering (up to 99.99% training accuracy).
• Assessed using clusters for income insights, highlighting the value of tailored classification models.

UNIVERSITY OF DENVER, SCHOOL OF ENGINEERING AND COMPUTER SCIENCE, Denver, CO

Master of Science – Data Science Graduated 2023

• 3.94 GPA.
• Calculus I, II, & III, Discrete Math, Linear Algebra, Python I & II, Probability & Statistics I & II, Algorithms, Data Visualization, Data Mining, Database Organization & Management, Parallel & Distributed Computing, Data Science Tools I & II, Machine Learning, Data Science Capstone.