This position is located in the Data Science Institute. DSI 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. If you are skilled in data science problem solving, enjoy working across a variety of data science tools, and committed to continuous learning and collaboration, consider joining our team!

This position will be located on the University of Arizona campus in Tucson, AZ.

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:

· INSTRUCTION AND MENTORING

- Prepare and teach new computational technologies and data science methods as just-in-time training as required to support research activities on campus.

- Engage, instruct, and interact with scientific collaborators and represent the UArizona Data Science Institute and CyVerse at national and international workshops and scientific conferences.

- Utilize domain specific experience and expertise to coordinate and administer specific training and research programs

- Utilize CyVerse, HPC and other University research computing systems to maximize efficient computational workflows

- Supervise and mentor graduate students in the DataLab, in training programs offered through the Data Science Institute and related to research projects.

- Use and follow best practices in developing training materials, scientific computing, data and code management, documentation and digital forms or communication

· RESEARCH APPLICATIONS

- Create, validate, and test scientific applications of data science algorithms, models, libraries and related software. Apply and test new computational technologies and data science techniques; report learnings to other staff in the Data Science Institute.

- Use and follow best practices with containers, computational notebooks, reproducible code, big datasets, edge computing, and distributed computing.

- Advise and assist investigators in determining the appropriate data science methodology and tooling to meet their research objectives

- Mentor and/or instruct research teams on use of data science methods, tools and best practices.

· OTHER DUTIES & SERVICE TO DEPARTMENT AND UNIVERSITY

- In support of our mission to extend and support the use of data science throughout campus:

§ Provides input on strategic planning, making recommendations for operation improvements to the unit, provides input on departmental programs and offer opportunities for growth and improvement.

§ Serve on committees in support of our mission.

§ Participate in outreach activities with campus and the broader UA community.

§ Serves as program liaison with campus and community partners

§ Represent the Data Science Institute at workshops, meetings and conferences.

§ Contributes, develops and leads University of Arizona data science community events such as Coffee & Code, Hacky Hour, Women in Data Science, and RezBaz events.

· Additional duties may be assigned.

Knowledge, skills & abilities:

· Problem-solving and data manipulation skills

· Able to use advanced organizational skills and knowledge to organize, manage, prioritize and work on multiple, dynamic projects; and fulfill assigned tasks and projects including learning new methods and technologies

· Able to successfully communicate to research, technical and lay audiences.

· 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 computational notebooks and demonstrated proficiency with one or more programming languages for data analysis

· Knowledge of best practices in data management for research projects

· 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 create community and trust with workshop participants

· Demonstrated ability to build community and/or communicate successfully with researchers and students from different disciplines

· Proficiency in R or Python

• Master’s degree in a data-analytic discipline (e.g., Data Science, Statistics, Computer Science, Mathematics, Engineering, or a data-driven disciplinary field), and a minimum of 5 years of relevant work experience, or equivalent combination of education and work experience.

• PhD degree in relevant field is preferred.
• Experience with hands-on, data science problem solving applying deep learning methods with complex data sets.
• Experience conducting research using one of the following: natural language processing, deep learning, image and/or video segmentation, or federated learning.
• Experience in projects involving advanced computing and information technologies used in science research, government laboratories and/or industry; experience using CyVerse is heavily preferred.
• Is a Carpentries Certified Instructor.
• Experience teaching one or more Software Carpentries Workshops.
• Instructional experience in workshop or classroom setting; including development of supporting curriculum materials.
• Formal project management experience.
• Knowledge and experience with open, reproducible research.