M.Eng. Computer Science Candidate · Oregon State University · Expected May 2027

Software engineer with graduate-level focus in artificial intelligence and machine learning. Incoming Computer Science Intern at Lam Research, with experience building scalable backend systems and full-stack applications.

Oregon State University M.Eng. in Computer Science — Expected May 2027 Coursework focus: Artificial Intelligence & Machine Learning

• Completing graduate coursework in AI/ML at Oregon State University
• Incoming Computer Science Intern at Lam Research (Summer 2026)
• Open to discussing AI systems, backend development, and data pipelines

Languages: Python · C++ · C# · JavaScript · TypeScript · Java · RISC-V Assembly

Frameworks & Libraries: React Native · Expo · NumPy · Pandas · Flask · Unity · Drizzle ORM · Zustand

Tools & Platforms: Git/GitHub · Docker · Linux · Node.js · SQLite · VS Code

Competencies: REST APIs · Unit Testing · Scalable Architecture · Data Structures & Algorithms · CI/CD

React Native · Expo · TypeScript · SQLite · Drizzle ORM

A production-ready mobile app built with a team, focused on privacy and usability. I owned the core cycle prediction algorithms, health insight visualizations, and daily logging features, and led optimization of the data persistence layer.

• Engineered the SQLite + Drizzle ORM data layer with optimized query design and schema planning
• Refactored component architecture and improved render performance using Zustand state management
• Drove UI/UX improvements through structured user testing and iterative design cycles
• Collaborated via Git workflows, PR reviews, and modular code practices

Python · NumPy · Pandas · Statsmodels

An end-to-end predictive modeling system that forecasts league standings using Poisson regression and Monte Carlo simulation. Built all data pipeline stages and evaluation tooling.

• Implemented Monte Carlo simulation engine running 5,000+ season simulations per prediction cycle
• Automated full data pipeline: ingestion, preprocessing, feature engineering, and model training
• Improved runtime through vectorized operations and efficient data structures
• Built statistical evaluation framework for measuring season-over-season prediction accuracy

Email: jonahsutch11@gmail.com LinkedIn: linkedin.com/in/jonah-sutch-031589293 Location: Corvallis, OR