Grinnell Chamber

Data Scientist: Data Analysis & Social Inquiry Lab

Full time
Posted: 01/04/2023
Grinnell, IA


Position Description
Grinnell College’s Data Analysis and Social Inquiry Lab (DASIL) helps students, faculty, and staff members integrate data-driven methodology and technology inside and outside of the classroom. DASIL exists as an academic resource at the intersection of social inquiry and data science. DASIL currently supports a variety of data-driven software packages and programming languages including ArcGIS, Bloomberg, Excel, Minitab, NVivo, Python, Qualtrics, R, SPSS, Stata, and Tableau. We play an integral role in supporting members of Grinnell College to tackle data in a variety of ways, including:
• Providing experiential learning for student employees through peer mentoring and project-based work
• Training students, faculty, and staff members to use data-driven software packages and programming languages
• Preparing datasets for use in classroom exercises and other pedagogical activities
• Collecting, analyzing, and visualizing data for faculty- and staff-led research

Duties & Responsibilities:
The Data Scientist of DASIL provides data-driven support for students, faculty, and staff members. They may provide support in the following ways:
• Consulting with members of Grinnell College about appropriate use of data collection, analysis, and visualization
• Designing classroom exercises and prepare accompanying datasets
• Developing systems of data acquisition and visualization
• Managing projects at the intersection of social inquiry and data science in collaboration with faculty and staff
The Data Scientist calls for the possession of technical expertise necessary to carry out data-driven projects. The activities of data-driven projects may vary from one to another, but they may involve:
• Automating the collection of data from open-source databases
• Creating interactive dashboards to gather insight and motivate inquiry
• Performing advanced analysis on data varying in structure (i.e., hierarchical groups, longitudinal studies)


A background in statistics, some coursework in the Social Sciences, appropriate programming skills, a willingness to expand skills as needed, and a Masters degree or higher in a relevant field are required. The successful applicant will have good communication skills with experience or interest in mentoring undergraduate students from diverse backgrounds and departments. Proficiency in Geographic Information Systems is desirable, but not required.

Applicable Skills
• ArcGIS
• Stata
• Minitab
• Excel
• Computer programming (Python experience preferred)
• NVivo
• R and RStudio (Advanced knowledge demonstrated through work and research preferred)
• Bloomberg
• Qualtrics
• Tableau

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