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About the Sorenson Impact Center
The Sorenson Impact Center with the David Eccles School of Business at the University of Utah envisions a thriving world where all people are valued, communities prosper, and the measured impact of our actions guides decision making. The Center advances global impact through innovation in impact investing and finance, public policy and government spending, and corporate and social sector behavior with organizations across the globe, and utilizes world-class data science, impact storytelling and collaboration as key tools. As part of its mission to train future impact leaders, the Center integrates academic programming and experiential learning into each of its practice areas.
Data Science student interns at the Sorenson Impact Center will take a more computational- and infrastructure-centric approach. We are open to applicants with an interest in data science but may not have been indoctrinated in a curriculum specific to data science studies. We encourage those with sound fundamentals in probability and statistics, programming, computer technology, engineering math, or have shown the ability to conduct quality research or developmental work in a quantitative field to apply. This client-facing work is always changing and new projects start frequently (watch a short YouTube video to learn more about what we do). We look for highly motivated self-starters who fit the criteria below.
- Build-out a core computational (cloud-centric) infrastructure
- Deepening capabilities in impact investing, impact finance, and post-secondary educational ecosystem
- Data science student interns work alongside the data science team and will gain an appreciation of how your abilities can contribute to the data science endeavor
- Learn new skills and concepts, and discover your place in this vast and unfolding field
- Engage with real-world clients while building their skills and portfolio
- Work in a fast paced, constantly changing environment
- Be proactive, innovative, and resourceful
- Demonstrate a “solutions-oriented” problem solver mentality
- Able to communicate complex information in a clear and understandable manner
- Have a curiosity approach and open to learn new methods
- Show ownership and mature responsibility
- Applicants must be proficient in R or Python, including familiarity with the tidyverse family of packages or Pandas
- Experience with Apache Arrow or data visualization frameworks (i.e. Shiny dashboard) preferred by not required
- Have at least a basic understanding of probability and/or statistical analysis
- Students must commit to working 20 hours per week for a minimum of two semesters
- Experience with git software preferred but not required
- Desire to work with dockers
*The dynamic nature of work means the student experience becomes more valuable with deeper levels of engagement. To facilitate this experience, students are expected to commit to working 20 hours per week for a minimum of two semesters (continuation beyond the first semester is dependent upon meeting the appropriate level of performance).
**The Sorenson Impact Center strongly encourages diverse applicants (please circulate widely), especially those who self-identify as Black, Native or Indigenous, People of Color, LGBTQIA+, non-binary, living with disabilities, neurodivergent, young, speak English as a second language, and others from overlooked / underestimated communities.
*** Due to legal restrictions regarding student employment under certain Visa statuses, Sorenson Impact can not guarantee our ability to pay international students. For international students potentially selected, we commit to working with you and your institution to determine our ability to adequately compensate you for your time and energy. Please reach out with any questions.Impact can not guarantee our ability to pay international students. For international students potentially selected, we commit to working with you and your institution to determine our ability to adequately compensate you for your time and energy. Please reach out with any questions.