Overview

Reporting to the Associate Director, Computational Methods and Data, within the department of Data and Research Innovation, the Computational Social Scientist leads the library’s support for computationally enabled social science research. This includes providing research consultations and designing and delivering instruction to students, faculty, and staff. The Computational Social Scientist may also develop and support research workflows, analytical approaches, and technology solutions in response to continual assessment of researcher needs and identification of emerging trends in computational social science.

The incumbent will participate in the development of a research and learning service model for data-intensive and computational social science research across disciplines based on current research practices, grounded in student and faculty academic needs, and aligned to Yale Library strategies. The incumbent will collaborate with other members of Data and Research Innovation to provide research support across the research data lifecycle and contribute to the development of innovative researcher and practitioner support programs, including novel approaches to research consultations, methodological community-building, research data support, reproducible research practices, responsible use of sensitive data, specialized instruction and outreach, and other research support activities. Activities are offered across multiple library locations, but primarily occur at the Franke Family Digital Humanities Lab, Rosenkranz Hall, and Marx Science and Social Science Library.

Required Skills and Abilities

1. Demonstrated understanding of computational approaches to social science research, including linking research questions to appropriate data and methods.
2. Demonstrated proficiency with advanced quantitative data analysis, methodology and related software (such as R, Python, Stata, etc.) in an academic setting.  
3. Demonstrated ability learning new methods and tools quickly, with reference to both scholarly literature and accepted practice.
4.  Demonstrated written and verbal communication skills, including conveying technical and methodological subjects to non-technical audiences. Demonstrated experience offering instruction on a technical or methodological subject, especially one-off or workshop instruction.
5. Demonstrated experience collaborating within and across organizations. Knowledge of and experience with relational databases. Demonstrated ability with survey design and related tools (such as Qualtrics or Survey Monkey).

Preferred Skills and Abilities

Principal Responsibilities

1. Conduct targeted outreach to faculty, students, and research staff to identify emerging needs in computational social science and connect them with relevant resources, datasets, and methods. 
2. Provide expert guidance on computational social science methods and workflows, including research design, data acquisition, data management, and analysis for social scientific questions. 
3. In collaboration with other members of Data and Research Innovation, advise researchers on reproducible and responsible research practices, including documentation, version control, privacy-aware workflows, and appropriate use of sensitive or human-subjects data in consultation with Yale’s HRPP. 
4. Design and deliver workshops, tutorials, and instructional sessions on computational social science topics, including working with digital trace data, computational approaches to political speech, graph analysis, automated de-identification, and more.
5. Create accessible learning materials such as written guides, tutorials, and interactive modules for independent learning on computational social science methods and tools. 
6. Contribute to the development and documentation of research support infrastructure, including shared analytic workflows, templates, and guidance for managing and analyzing social science data in collaboration with library and IT staff. 
7. Facilitate partnerships across departments and research centers and participate in cross-institutional communities of practice related to computational social science. 
8. Stay current with methodological and tool developments (eg. new approaches in NLP, LLM-assisted analysis, platform/API changes, and best practices for responsible data use) and translate complex concepts into accessible formats for diverse audiences, including library staff.

Required Education and Experience

1. PhD in the social sciences, or master’s degree in the social sciences and four years of experience in an academic environment, or equivalent combination of education and experience.

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