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    Daniel Klein

    Data Scientist focused on networks, platforms, and relational data

    Daniel Klein is a versatile professional with expertise in full-stack data science, encompassing areas from lab-based research to making informed decisions. With a blend of computational, practical, and theoretical knowledge, Daniel excels in understanding the scalability of solutions from small to large datasets, ensuring applicability across different magnitudes of data.

    His specialties include data analysis, statistical analysis, algorithms, and mathematical modeling. Daniel's academic background is impressive, having pursued a Doctor of Philosophy (Ph.D., ABD) degree in Applied Mathematics from Brown University and a BA in Mathematics and Biology from Williams College.

    Throughout his career, Daniel Klein has held various significant roles. He has served as the Principal Data Scientist at Moat, Senior Software Engineer at BlockSeer, Data Scientist at RealScout, and as an Apprentice Consultant (Data Science) at Catenus Science. He also has experience as a Graduate Student and Assistant Scientist at Brown University, bringing a rich blend of academia and practical experience to his professional roles.

    His experience extends to research internships at the University of Minnesota, where he honed his skills further in scientific computation, underlining his dedication to continuous learning and growth in the field of data science.

    Daniel Klein
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    Location

    New York, New York, United States
    Location