Description
The Arthur J. Morris Law Library at the University of Virginia School of Law seeks a Legal Data Scientist to lead and manage its Legal Data Lab. As leader and manager of the Legal Data Lab, the Legal Data Scientist will work closely with the Library Director and Law School faculty to develop and implement the Legal Data Lab’s strategic vision. The Legal Data Scientist’s primary role will be to support complex research initiatives requiring the collection, cleaning, organization (e.g., web scraping, data manipulation, etc.), storage, and digital dissemination of legal and other datasets in support of the empirical scholarship of the faculty at the School of Law.
The Legal Data Scientist will engage in student instruction, including one-on-one, small group, guest lecturing, and possibly teaching short-form courses for credit. While supporting the scholarship and educational needs of faculty and students will be the primary focus of the position, there will be some opportunity for independent research, writing, and professional engagement in the library, empirical research, data science, and/or other relevant academic communities. Depending on Law School needs and the knowledge and experience of the successful candidate, faculty scholarship support and student instruction topics may include statistical analysis and/or machine learning and natural language processing. This position requires most work to be performed in person at the Law School, with the opportunity to perform a limited amount of work remotely in accordance with Law School policy.
Requirements
Required Qualifications:
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A doctoral degree or master’s degree with significant experience.
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Proficiency with Python and/or R programming languages.
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Strong technical skills and problem-solving abilities related to data collection and cleaning.
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Demonstrated experience with web scraping, electronic document parsing, and using APIs to fetch data. Knowledge of HTML and JavaScript sufficient to confidently extract data from websites.
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Demonstrated experience with data wrangling, such as merging, reshaping, or manipulating data using regular expressions.
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Strong oral and written communication skills.
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Ability to manage multiple projects and produce deliverables in a timely fashion.
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Strong attention to detail and quality of work product.
Preferred Qualifications:
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Master’s degree or higher in computer/information/data science or an applied social science field.
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Demonstrated experience with machine learning and natural language processing and/or statistics.
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Familiarity with Stata.
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Familiarity with distributed version-control systems (e.g., Git and GitHub).
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Familiarity with Unix and Unix-based systems. Comfort in using the command line.
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Familiarity with legal information or a willingness to learn.
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Experience working with and supporting faculty across the lifecycle of empirical research projects (e.g., project design, data collection, analysis, dissemination, storage).
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History of managerial and supervisory success.
