Melissa McHann

Insightful Data Scientist recognized for high productivity and efficient task completion. Skilled in machine learning, big data analytics, and statistical modeling to deliver actionable insights. Strong in communication, problem-solving, and teamwork, enabling successful collaboration across departments to drive projects to completion.

Malware Infection Classification Model, Built a classification model to predict malware infection., Loaded the dataset using Pandas and explored data distributions to understand feature behavior., Handled missing values and applied dimensionality reduction techniques such as PCA and feature selection., Converted categorical variables to numerical format using one-hot encoding., Designed new features to boost model performance, leveraging domain knowledge and creativity., Split the data into training and validation sets using stratified sampling to account for class imbalance., Trained models using algorithms such as Logistic Regression, Random Forest, and Gradient Boosting, optimized for large datasets., Evaluated models using metrics like accuracy, precision, recall, F1-score, and AUC-ROC, addressing class imbalance challenges., Generated predictions on the test dataset, delivering actionable insights for malware detection. SQL Soccer Database, Designed and implemented a comprehensive SQL database for soccer data, enhancing data accessibility and analysis. Machine Learning for Business Problems, Applied various ML algorithms (kNN, Bayesian, Decision Trees, SVM, Neural Networks) to develop models solving unique business challenges. Web Development, Built dynamic websites using HTML, CSS, JavaScript, React.js, and deployed them on local and cloud-based virtual machines. Cancer Data Analysis, Integrated and analyzed data from multiple public databases, investigating associations between risk factors and cancer diagnoses.

• Honors College, Texas Tech University
• National Society of Leadership and Success
• President’s List