The University of Virginia School of Law seeks highly qualified applicants for a Statistical Research Specialist. This is a Senior Professional Research Staff position with the classification of Research Scientist. Reporting to the Head of the Legal Data Lab, the Statistical Research Specialist is a core position for the law library’s ongoing efforts to support empirical legal scholarship at the University of Virginia School of Law. As a vital member of one of the few such labs in the country, the Statistical Research Specialist will have a direct impact on strategy and planning for the Lab as well as continuing support for faculty research. The University’s newly created School of Data Science makes this a particularly interesting time in legal scholarship at the University and we anticipate many exciting opportunities.
The Statistical Research Specialist will assist faculty and other library patrons with complex research initiatives involving basic and advanced statistical techniques and provide consulting and assistance with statistical software programs, study design, data collection, and various forms of analysis. Some reference service, analysis of library operations data, and occasional lecturing will be required. Participation in the statistical and data science communities of the University of Virginia will be expected.
Requirements include: Significant course work in statistical methods; considerable experience in the application of quantitative methods to social science, business, and/or legal data; proficiency with a range of statistical software packages, particularly Stata and R; and the ability to work and communicate effectively orally and in writing with the University of Virginia School of Law community. Some experience with machine learning and natural language processing techniques is preferred. A demonstrated ability to visually represent data for academic publication is a plus.
Candidates must have at a minimum a M.S. in a relevant discipline (e.g., Economics, Political Science, Statistics). A Ph.D. is preferred but not required.
Salary is commensurate with experience and qualifications.
Introduction to R
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.
One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.
R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.