Continuing Lecturer at Capital Data Corp. of Austin
Austin, Texas, United States
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Summary
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Senior
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Top School
Gunnar Kleemann is a data science educator and practitioner with 11 years of experience applying high-power analytics to large, complex datasets across academia, biotech, and consulting. Based in Austin and Berkeley, he teaches master’s-level data science at UC Berkeley while leading AI research and data science services through the Berkeley Data Science Group and his firm, Capital Data Corp. His toolkit spans Python, R, Matlab, cloud platforms (AWS, SoftLayer), big-data tooling and experimental design, with domain depth in genomics and assay automation from years in laboratory research and bioinformatics. Gunnar has translated hands-on wet-lab expertise into scalable data workflows—wrangling 10s–100s of GB datasets, building ML models for biotech and commercial problems, and developing visualization and automation tools. He blends rigorous academic training (PhD in Molecular Genetics, postdoc in genomics) with practical product and teaching experience, mentoring students and teams across bootcamps and graduate courses. An often-overlooked strength is his ability to bridge protocol-level lab automation with cloud-scale analytics, enabling reproducible, end-to-end scientific data products.
11 years of coding experience
16 years of employment as a software developer
Master’s Degree Data Science, Master’s Degree Data Science at University of California, Berkeley
Ph. D. Molecular Genetics, Ph. D. Molecular Genetics at Albert Einstein College of Medicine
B.S. Biology/Biological Sciences General, B.S. Biology/Biological Sciences General at Syracuse University
Post-doctoral trainee Genome Sciences/Genomics, Post-doctoral trainee Genome Sciences/Genomics at Princeton University
Master's Degree Ecology and Evolutionary Biology, Master's Degree Ecology and Evolutionary Biology at University of Nebraska-Lincoln
Contributions:14 PRs, 127 pushes, 1 branch in 6 years 2 months
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