We present the development and validation of the Higgs Optimized b Identification Tagger (HOBIT), a multivariate b-jet identification algorithm optimized for Higgs boson searches at the CDF experiment at the Fermilab Tevatron. At collider experiments, b taggers allow one to distinguish particle jets containing B hadrons from other jets; these algorithms have been used for many years with great success at CDF. HOBIT has been designed specifically for use in searches for light Higgs bosons decaying via H→bb̄. This fact combined with the extent to which HOBIT synthesizes and extends the best ideas of previous taggers makes HOBIT unique among CDF b-tagging algorithms. Employing feed-forward neural network architectures, HOBIT provides an output value ranging from approximately -1 (light-jet like) to 1 (b-jet like); this continuous output value has been tuned to provide maximum sensitivity in light Higgs boson search analyses. When tuned to the equivalent light jet rejection rate, HOBIT tags 54% of b jets in Monte Carlo simulated Higgs boson events (mH=120 GeV/c2) compared to 39% for SecVtx, the most commonly used b tagger at CDF. We present features of the tagger as well as its characterization in the form of b-jet finding efficiencies and false (light-jet) tag rates. © 2012 Elsevier B.V.