James Tyler

Background

About James Tyler

I am a recent Data Science graduate from the University of New Hampshire with a focus on using machine learning and analytics to solve real-world problems. My interests lie in human performance, health, and strategic systems. For my senior capstone, I led a team developing machine learning models to classify posture and pitching mechanics using IMU sensor data. We achieved 97 percent pitch prediction and 95 percent posture classification accuracy. This work supports applications in biomechanics, rehabilitation, and sports performance. I have built full machine learning pipelines from raw data collection and cleaning to model training, validation, and delivery of actionable insights. At the UNH InterOperability Lab, I progressed through several roles and most recently worked as a Data Science Intern. I built forecasting models that improved customer renewal prediction accuracy by 21 percent, developed interactive dashboards for strategic planning, and collaborated with both internal leadership and clients such as Intel and Microsoft. I also mentored new team members and contributed to compliance testing pipelines aligned with federal standards. Outside of work, I am interested in how data can improve long-term decision-making and human outcomes. These include areas such as healthcare, rehabilitation, simulation-based strategy, and system design. I think in terms of systems, whether optimizing workflows in machine learning or balancing resource paths in games. I aim to build solutions that are accurate, scalable, and easy to use. I am currently seeking full-time opportunities where I can apply data science, machine learning, and strategic thinking to high-impact domains such as health technology, artificial intelligence for human factors, and advanced R&D environments. Feel free to connect. I am always open to collaborating, learning, or discussing how data can be used to solve meaningful, real-world problems.