Mike Tamir



Mike serves as Chief Data Science Officer at Takt and lecturer for UC Berkeley iSchool Data Science masters program.  Mike has led several teams of Data Scientists in the bay area as Chief Data Scientist for InterTrust, Director of Data Sciences for MetaScale, and Chief Science Officer for Galvanize he oversaw all data science product development and created the MS in Data Science program in partnership with UNH.  Mike began his career in academia serving as a mathematics teaching fellow for Columbia University and graduate student at the University of Pittsburgh. His early research focused on developing the epsilon-anchor methodology for resolving both an inconsistency he highlighted in the dynamics of Einstein’s general relativity theory and the convergence of “large N” Monte Carlo simulations in Statistical Mechanics’ universality models of criticality phenomena.



Ph.D.    Phil. of Physics, University of Pittsburgh: Foundations of General Relativity and AQSM

M.A.    Mathematics, University of Pittsburgh: Differential Geometry & Operator Algebras

M.S.    Physics, University of Pittsburgh: Relativity Theory & Algebraic Quantum Field Theory

B.A.    Pure Mathematics, Columbia University: Combinatorial Number Theory & Probability

B.A.    Philosophy, Columbia University: Mathematical Logic & Phil. of Physics

Last updated:

November 22, 2017