Hello! I'm Kenzie Baker, a passionate full-stack software developer with a strong background in computer science and data science. I graduated from Michigan Tech University (MTU) with a Bachelor of Science in Computer Science in 2023 and completed my Master's in Data Science, also from MTU, in 2024. Additionally, I hold a minor in Statistics and an Applied Statistics certificate.
Currently, I am leveraging my skills as a full-stack developer at Service Express, a leading data center solutions company, where I contribute to the Sales and Marketing Development Team. My experience spans over three years in software development, and I thrive on tackling complex challenges and crafting innovative solutions.
- Python
- R
- PHP
- ASP Classic
- C
- JavaScript
- HTML
- CSS
- SAS
- SQL
- Node.js
- Vue.js
- Smartpods
- Extensive experience in machine learning and predictive modeling
- Proficient in data analysis, visualization, and interpretation
- Responsibilities:
- Addressing bugs and issues in existing systems.
- Developing new features and enhancements for internal tools and applications.
- Optimizing codebase for performance and scalability.
- Technologies Used: SQL, PHP, Golang, Vue.js, JavaScript, HTML, CSS, ASP Classic.
- Led a cross-functional team in the development of the Health Harbor Application, a comprehensive wellness system.
- Oversaw the implementation of smartpods, Node.js, React, JavaScript, and other technologies to ensure the system's functionality and scalability.
- Managed project timelines, resources, and deliverables to ensure successful project completion within scope and budget.
- Created and presented business funding proposals
- Objective: Developed a virtual machine environment for public health disease surveillance.
- Description: Configured virtual machines for four hospitals and one Health Information Exchange (HIE) to facilitate secure data exchange and analysis. Utilized provided operating systems compatible with OpenEMR for hospitals and HAPI-FHIR for the HIE. Implemented OpenEMR as the Electronic Health Record (EHR) system for each hospital and generated synthetic patient and syndromic surveillance data using Synthea for disease outbreak surveillance.
- Technologies Used: Virtualization technologies, OpenEMR, Synthea, HAPI-FHIR.
- Skills Demonstrated: Proficiency in system configuration, healthcare informatics, data generation, and interoperability standards.
Certainly! Here's a project description for your "Predicting Round Winner in Competitive CS:GO" final project:
- Objective: Developed a predictive model to forecast the outcome of rounds in competitive Counter-Strike: Global Offensive (CS:GO) matches.
- Description: Utilized big data analytics techniques to analyze gameplay data, player statistics, and match outcomes from competitive CS:GO matches. Leveraged machine learning algorithms to build a predictive model capable of identifying factors influencing round outcomes and forecasting the winning team for each round.
- Methodology: Collected and preprocessed large datasets containing gameplay events, player actions, and match results. Conducted exploratory data analysis to identify relevant features and patterns in the data. Developed and trained machine learning models, such as logistic regression, decision trees, or neural networks, to predict round winners based on historical data. Evaluated model performance using metrics such as accuracy, precision, recall, and F1 score.
- Technologies Used: Big data analytics tools (e.g., Apache Spark, Hadoop), machine learning libraries (e.g., Scikit-learn, TensorFlow), programming languages (e.g., Python), data visualization tools (e.g., Matplotlib, Seaborn).
- Outcome: Generated insights into the key factors influencing round outcomes in CS:GO matches and provided a predictive tool to assist teams in making strategic decisions during gameplay.
- Master of Science in Data Science, Michigan Tech University, 2024
- Bachelor of Science in Computer Science, Michigan Tech University, 2023
- Minor in Statistics, Michigan Tech University, 2024
Feel free to reach out to me via email or connect with me on LinkedIn.
Thank you for visiting my portfolio! I'm excited to continue learning and contributing to impactful projects in the world of technology and data science.