Summary
Karlen Shahinyan is a data scientist and former astrophysics researcher with 11 years of experience turning complex, noisy datasets into actionable insights. Based in Portland, Oregon, he has built and deployed ML models across healthcare wearables, manufacturing process optimization, and spatial safety applications, translating domain knowledge into validated, production-ready solutions. His background in astrophysics led large multi-institution collaborations, automated analysis pipelines, and Monte Carlo significance testing—skills he now applies to clinical trials, device validation (resulting in conference presentations, a journal publication, and three patent filings), and applied industry problems. Karlen coaches and mentors data scientists through immersive programs, emphasizing model evaluation, storytelling, and reproducible pipelines. He combines signal-processing and feature engineering strengths with practical deployment experience (AWS, Flask) and a knack for simplifying messy real-world data into reliable metrics. Colleagues rely on him to bridge domain expertise and engineering rigor to deliver high-impact, evidence-backed solutions.
11 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy - PhD, Astrophysics, Doctor of Philosophy - PhD, Astrophysics at University of Minnesota
Bachelor of Arts - BA, Astronomy, Physics, Philosophy, Bachelor of Arts - BA, Astronomy, Physics, Philosophy at Wesleyan University
Armenian, Russian