Elle Najt
About Elle Najt
Elle Najt is a Data Scientist with a Ph.D. in Mathematics from the University of Wisconsin-Madison. She has experience in statistical applications of Markov chains and has worked at institutions such as Los Alamos National Laboratory and Two Sigma.
Current Role as Data Scientist
Elle Najt currently serves as a Data Scientist at Two Sigma, a position she has held since 2022. Located in Manhattan, New York, she applies her expertise in data science to various projects. Her role involves leveraging statistical methods and mathematical concepts to solve complex problems in data analysis and interpretation.
Previous Experience at Two Sigma
Prior to her current role, Elle Najt worked at Two Sigma as a Data Scientist from 2021 to 2022 for a duration of seven months. During this time, she contributed to research focused on the statistical applications of Markov chains. Her work involved utilizing advanced data science techniques to enhance the understanding of data-driven decision-making.
Research Experience at Los Alamos National Laboratory
Elle Najt gained research experience as a Graduate Student Researcher at Los Alamos National Laboratory in 2020. This position lasted four months and took place in Los Alamos, New Mexico. Her work during this time contributed to her understanding of data science applications in a national laboratory setting.
Education and Expertise in Mathematics
Elle Najt earned her Doctor of Philosophy (Ph.D.) in Mathematics from the University of Wisconsin-Madison, where she studied from 2014 to 2021. Her doctoral research focused on Markov chains, combinatorics, algorithms, and their applications to statistics and political redistricting. She also holds a Bachelor's degree in Mathematics from Carleton College, where she studied from 2009 to 2013.
Expertise in Political Redistricting
Elle Najt has developed expertise in applying mathematical concepts to political redistricting. Her academic background and research experience have equipped her with the skills necessary to analyze and interpret data related to electoral districting, contributing to discussions on political representation.