Posted to IASSIST on: 2019-05-08
Employer: Dartmouth College
Employer URL: https://home.dartmouth.edu/
Description
Designed for someone beginning their career in data science, the Data Fellow will work with Dartmouth students and researchers in finding, manipulating, analyzing, and visualizing statistical data. With guidance and supervision, this person will develop and offer consultation and other services on appropriate tools and software (such as R and Stata). With a focus on Dartmouth’s business, engineering, and economics communities, this individual will collaborate with other librarians and data professionals, and will contribute to Dartmouth Library’s emerging data services program.
During the two year fellowship, this individual will be encouraged to pursue opportunities to learn new skills, methods, and software; to develop and complete an independent project; and to present on a relevant topic at a professional association conference at the end of their two years.
MINIMUM QUALIFICATIONS
- Bachelor’s degree in the data sciences, the social sciences, computer science, statistics, applied math, financial engineering, business, or other relevant field.
- Familiarity with data science concepts and approaches, as evidenced by work experience or educational background.
- Basic skills or experience with at least one of the following tools, software packages, or programming languages: R, Stata, SPSS, SAS, MatLab, Python, or Julia.
- Strong interpersonal, organizational, and communication skills.
- Demonstrated interest in, and enthusiasm for, outreach, service and support for user communities.
- Aptitude and motivation for self-directed learning, experimentation, and discovery.
- Commitment to diversity and to supporting the needs of a diverse population.
PREFERRED QUALIFICATIONS
- Demonstrated experience using complex machine-readable statistical and/or geospatial data such as U.S. Census, financial, or economic data.
- In-depth knowledge of R, Stata, SPSS, SAS, MatLab, Python, or Julia.
- Programming ability.
Archived on: 2020-01-07