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Penny Ahlstrom

Penny Ahlstrom

Software developer focused on building practical solutions that improve workflows, solve real problems, and make technology easier to use. I have a strong foundation in machine learning, data analysis, and full-stack development, with experience in building data-driven applications, including Python-based machine learning models and full-stack systems using modern web technologies.
My background in biostatistics and biological research allows me to approach problems analytically, while my programming experience enables me to translate complex ideas into practical solutions. I am particularly interested in applying machine learning and data-driven approaches to real-world problems.
Browse my portfolio to learn more about me, explore my work, or watch a walkthrough of the site.

Career Summary

  • Built Java (Spring Boot) microservices with REST-based communication, Docker containerization, and integration testing using TestContainers.
  • Developed full-stack applications using React, Node.js, Express, and MongoDB, implementing authentication, CRUD functionality, and API integration.
  • Designed and implemented RESTful APIs to support data-driven applications, including search and filtering features.
  • Built and evaluated machine learning models in Python (scikit-learn) for classification and regression tasks, applying preprocessing, feature engineering, and cross-validation techniques.
  • Trained and tested neural networks (TensorFlow/Keras), experimenting with architecture and hyperparameters to understand model performance and generalization.
  • Streamlined data processing workflows using Excel, reducing manual effort by approximately 40–50% across datasets of 1,000+ records.
  • Conducted research applying statistical analysis and R, resulting in a Thesis Prize nomination.

Get in Touch

If you're interested in collaborating, discussing a project, or learning more about my work, I would be happy to connect.