Summary
Alex Naka is a machine learning engineer focused on protein engineering, combining a decade of data science experience with a PhD in neuroscience and hands-on experimental expertise. He brings fluency in Python and a strong foundation in statistical modeling, Bayesian approaches, and experimental design honed through postdoctoral and industry roles at Genentech, CODA Biotherapeutics, and longevity startup Loyal. At Science he applies generative and data-driven methods to biological problems, leveraging prior work building custom optogenetics hardware and analysis pipelines to bridge wet-lab experiments and computational models. Known for clear data visualization and cross-disciplinary collaboration, he also codes recreationally—his GitHub bio hints at interests spanning data, neuro, protein science, generative art, and dogs—suggesting a creative approach to technical problems.
9 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Neuroscience, Doctor of Philosophy - PhD, Neuroscience at University of California, Berkeley
Bachelor of Arts - BA, Biology; Psychology, Bachelor of Arts - BA, Biology; Psychology at Northwestern University