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!
The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here.
Duties & Responsibilities
Duties & Responsibilities:
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 Qualifications
Minimum of 5 years of relevant work experience is required. Master's Degree required.
Preferred Qualifications
- 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
FLSA
Exempt
Full Time/Part Time
Full Time
Number of Hours Worked per Week
40
Job FTE
1.0
Work Calendar
Fiscal
Job Category
Research
Benefits Eligible
Yes - Full Benefits
Rate of Pay
$65,000-$68,000 DOE
Compensation Type
salary at 1.0 full-time equivalency (FTE)
Grade
9
Career Stream and Level
PC3
Job Family
Research & Data Analysis
Job Function
Research
Type of criminal background check required:
Fingerprint criminal background check (security sensitive due to job duties)
Number of Vacancies
2
Target Hire Date
Expected End Date
Contact Information for Candidates
Maliaca Oxnam
maliaca@arizona.edu
Open Date
9/22/2021
Open Until Filled
Yes
Documents Needed to Apply
Curriculum Vitae (CV) and Cover Letter
Special Instructions to Applicant
Diversity Statement
At the University of Arizona, we value our inclusive climate because we know that diversity in experiences and perspectives is vital to advancing innovation, critical thinking, solving complex problems, and creating an inclusive academic community. As an Hispanic-serving institution and a Native American/Alaska Native-serving institution, we translate these values into action by seeking individuals who have experience and expertise working with diverse students, colleagues, and constituencies. Because we seek a workforce with a wide range of perspectives and experiences, we provide equal employment opportunities to applicants and employees without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or genetic information. As an Employer of National Service, we also welcome alumni of AmeriCorps, Peace Corps, and other national service programs and others who will help us advance our Inclusive Excellence initiative aimed at creating a university that values student, staff and faculty engagement in addressing issues of diversity and inclusiveness.
