Data Scientist

Work Arrangement: Hybrid (On-Site and Remote mix)

The Duke Law Library’s Data Lab is seeking a talented Data Scientist. The Data Lab plays a vital role in supporting the empirical research needs of Law School faculty, students, and staff, providing a broad range of skills to support each stage of the empirical research lifecycle. The Data Scientist will strengthen the Data Lab’s ability to create, manage, and share research-ready data and analysis resources that empower faculty, staff, and students in their work.

Reporting to the Assistant Director for Empirical Research and Data Services, and collaborating closely throughout the Law School and Law Library, the Data Scientist will guide law faculty and students in selecting appropriate methodologies and best practices for each phase of empirical research projects. For select initiatives, the Data Scientist will design and implement data preparation workflows tailored to meet project requirements accurately and efficiently.

Additionally, the Data Scientist will contribute to ERDS’s mission of promoting data literacy within legal scholarship and practice at Duke Law, while actively engaging with colleagues across the broader Duke University community.

• Assist faculty and students in selecting appropriate methodologies across the entire lifecycle of an empirical project, including research design, data capture, data management, data cleaning, analysis, presentation of results, replicability, and archival.
• Coordinate and monitor the design, development, modification, and implementation of information technology applications to combine, manipulate, and transform datasets of varying size, scope, and substance into formats that allows researchers to more easily view, interpret, and analyze data.
• Extract, clean, and organize raw information harvested from different electronic and web-based sources—including social media platforms, websites, and PDF documents.
• Use programmatic API calls to automate the collection and management of research data sources.
• Use, apply, and develop AI-powered research tools, using techniques such as machine-learning, large language models (LLMs), and natural language processing (NLP).
• Provide support for grant applications and IRB applications related to empirical research projects.
• Supervise and direct the performance of one or more student research assistants.
• Participate in development of long-range planning for and prioritization of new and existing projects.
• Ensure that external and internal regulations and policies governing data management are met including regulations concerning security, auditability, and privacy.
• Advise students, faculty, and staff on the use of data management concepts and tools—in and/or outside a classroom setting.
• Participate in a lively community of research and data support professionals at Duke University and the broader Research Triangle area.
• Perform other duties as assigned.

Education/Training: Work requires knowledge and skills generally acquired through completion of a Bachelor's degree program in business, computer science, mathematics, statistics or social sciences.

Experience: Work requires knowledge of both statistical analysis and interpretation generally acquired through at least two years of relevant experience.

OR AN EQUIVALENT COMBINATION OF RELEVANT EDUCATION AND/OR EXPERIENCE.

• Statistical analysis
• Proficiency in Python and/or R programming languages
• Machine learning
• Natural Language Processing (NLP)
• Excellent oral and written communication skills
• Demonstrated interpersonal and teamwork skills complemented by the ability to take initiative
• Independent active learning

• Advanced degree in computer/data science or an applied social science field

• 2 to 4 years of progressive data science experience, including: data capture, cleaning, and analysis; machine learning and NLP; programming; database administration experience, to include design, implementation, tuning, backup, recovery, modification and reorganization of relational databases.
• Strong technical skills and problem-solving abilities related to research data…