Jami Mulgrave

Jami Mulgrave, Ph.D., is a Research Scientist in the People Analytics group at Meta (formerly Facebook), with a strong background in Statistics and a focus on computational data analysis.

Jami's research experience includes leveraging computational tools to analyze electronic medical records data, and developing Bayesian nonparametric methods for learning graphical model structures.

Jami has participated in the Columbia Technology Ventures Fellowship program and has a keen interest in exploring the convergence of music, statistics, and machine learning in personal projects.

With a diverse educational background, Jami holds a Ph.D. in Statistics, a Master's degree in Statistics with a concentration in Statistical Genetics, and a Bachelor of Arts in Psychology with a concentration in the Premedical Sciences.

Proficient in a variety of programming languages and tools such as R, MATLAB, Python, SQL syntax, SAS, JMP Scripting Language (JSL), SAS Visual Analytics, SSPS, and UNIX.

Jami's work experience spans across various roles at organizations like Meta, Columbia University, AT&T Labs, SAS, First Analytics, and Memorial Sloan-Kettering Cancer Center, with internships at BlackRock, Barclays, and Warner Music Group.

Overall, Jami Mulgrave's expertise lies in statistical analysis, data science, and machine learning, with a unique passion for integrating music with machine learning algorithms.