paid / full-time / Tucson, AZ USA
The Data Science Institute at the University of Arizona is in search of Computational and Data Science Educators (Data Scientist III). This position will develop, enhance and expand the Data Science Institute’s capabilities to develop curriculum, workshops and just-in-time training in digital and computational science skills. The candidate will collaborate broadly across the data science community, including with other campus partners and trainers related to computational science and data science, such as CyVerse, High Performance Computing, University Libraries and various college/department efforts. The primary purpose of the position will be to provide just-in-time training, workshops consultation and support for students, faculty and staff wanting to learn foundational tools and concepts of data science and reproducible computational science.
The Data Science Institute aims to solve complex problems through data science collaborations with campus researchers and faculty and to build greater capacity for the use of data science throughout campus. Members of the Data Science Institute work closely with many campus partners and research teams. This position will be located on the University of Arizona campus in Tucson, Arizona.
Outstanding UA benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; state and optional retirement plans; access to UA recreation and cultural activities; and more!
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BUILD COMPUTATIONAL AND DATA SCIENCE CAPACITY THROUGHOUT CAMPUS (65%) :
- Develop and deliver workshops and related training materials on computational science and data science. Workshop topics may include but are not limited to computational notebooks, tools for reproducible computing, machine learning, data visualization, and data science applications and data management practices for big data.
- Work with campus partners and other trainers in delivery of workshops and training materials related to data science. Campus partners may include Research Computing/High Performance Computing, University Libraries, College of Agriculture and Life Sciences Data Science Team, CyVerse and others.
- Participate with and offer trainings for programs such as the Data Science Ambassadors, Roots for Resilience Graduate Fellowship and the Data Science Fellows programs.
- Use and follow best practices in developing training materials, scientific computing, data and code management, documentation and digital forms or communication
CONSULTATION, OUTREACH AND ENGAGEMENT ACTIVITIES (20%):
- Provides consultation on data acquisition, data management, computational programming in R and/or Python, and data visualization.
- Engage and interact with campus collaborators and related professional organizations; represent the Data Science Institute at workshops, meetings and conferences.
- Contribute to University of Arizona data science community events such as Coffee & Code, Hacky Hour, Women in Data Science, RezBaz, and Machine Learning Literacy Project events.
APPLIED DATA SCIENCE (10%):
- Apply and test new computational technologies and data science techniques; report learnings to other staff in the Data Science Institute.
- Provide consultation on use of new data science applications, including scientific software, virtualization, machine learning, data visualization, and other data science applications
INSTITUTIONAL OPERATIONS AND RELATED DUTIES (5%):
- Participate in department operational meetings, strategic planning and the like.
- Additional duties may be assigned.
Knowledge, skills & abilities:
- Able to perform computational analysis on large datasets involving advanced computing (high performance, distributed computing infrastructure) and information technologies used in science research, government laboratories and/or industry
- Able to perform analyses with machine learning, natural language processing and/or image processing
- Able to use R, RStudio, Python and/or Julia for data analysis
- Knowledge of best practices in data management for research projects
- Knowledge and experience with open, reproducible research
- Knowledge of best practices for leading and facilitating workshops and instruction sessions of a technical nature - Able to communicate advanced computational concepts into simpler, smaller components for instruction.
- Able to plan workshops and training
- Able to organize and host workshop logistics
- Able to create community and trust with workshop participants
- Knowledge and ability to use assessment techniques to improve workshops and trainings offered
- Oral presentation and communication skills
- Written communication skills, including preparing workshop materials and documentation
- Ability to communicate easily with scientists and students from various disciplines
- Ability to build community
- Strong organizational skills
- Ability to work independently under established deadlines and in a collaborative team
- Interest in and ability to rapidly test new technologies related to data science and analytics
Minimum of 5 years of relevant work experience is required.
Master's Degree required.
- PhD degree in relevant field is preferred.
- Programming experience in one or more of the following, Python, R, GO, C, C++, Java, Julia
- Experience teaching in a high school, college or university setting
- Experience using code and document versioning systems (e.g. Git, GitHub, GitLab)
- Experience in projects involving advanced computing (high performance, distributed computing infrastructure) and information technologies used in science research, government laboratories and/or industry.
- Experience with RStudio and/or Python for data analysis
- Experience performing analyses with machine learning, natural language processing and/or image processing
- Holds status as a Carpentries Certified Instructor
- Experience teaching one or more Software Carpentries Workshops and/or has contributed to the Software Carpentries curriculum
- Experience teaching in a workshop format
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