Professor of Practice in Data

The Connolly Alexander Institute for Data Science (CAIDS) seeks to hire a Professor of Practice in Data who will teach introductory and multi-disciplinary courses in data literacy presentation management and/or analysis. CAIDS promotes teaches and supports data literacy and data science for students faculty and the community. CAIDS programming includes courses workshops events student internship and co-curricular experiences research grants interdisciplinary research groups and statistical consulting. For more information on CAIDS see .

This position has a teaching load of two courses per semester (i.e. a 2/2) which is the same teaching load as most tenure-track faculty at Tulane University. The Professor of Practice will be expected to teach DATA 1010 Introduction to Data. This course seeks to be accessible to students of all backgrounds and abilities and will teach them fundamental skills in data literacy analysis communication and ethics. The Professor of Practice will also develop and teach one or two multi-disciplinary courses in data analysis presentation ethics or management in their areas of interest or expertise. This position is a permanent one with contracts renewed every three or five years. Renewal is based on an evaluation of teaching service and research (if part of the negotiated workload).

In addition to teaching the Professor of Practice will develop and facilitate aspects of CAIDS programming or services around increasing the participation of faculty and students across CAIDSs existing and new programs while upholding CAIDSs mission of being inclusive to all data fields. Based on the candidates expertise possible service roles may include developing and coordinating internal and external internship programs research assistant programs grant coordination developing and coordinating workshops and data-thons student group advising fostering partnerships with community organizations and community outreach partnerships (e.g. K-12 educational programming) overseeing annual programming such as the annual data theme and Love Data Week or supporting interdisciplinary research groups in the Professor of Practices area(s). The Professor of Practice will also have a role in helping direct and manage the focus and trajectory of CAIDS as an active and key partner. Conducting research is not a requirement for the Professor of Practice position but data-related research or scholarship on data science teaching and learning can be incorporated into the workload. This deviates from most other Professor of Practice positions which do not provide time for research.

Required Education and Experience

• A Ph.D. in a field of study that relates to data* and teaching experience as an instructor or teaching experience in a data-focused course; OR
• A Masters degree in a field of study that relates to data* with at least five (5) years of combined experience teaching in higher or secondary education and/or working in industry or government in a data literacy data analysis or data management position.
• *Related fields are those that conduct data analysis or management and applied statistics which includes but is not limited to statistics (preferably applied) quantitative social sciences (e.g. economics sociology political science psychology public or business administration) geography and related fields that use GIS (geographic information systems) computer science public health or medicine humanities with a data focus (e.g. digital humanities) education with a data focus and numerous STEM fields. Those with a background in qualitative research methodology will also be considered so long as they are able to teach basic quantitative methods in addition to qualitative methods.

Required Knowledge Skills Abilities/Competencies Typically needed to Perform This Job Successfully:

1. Demonstrated ability to teach in post-secondary institutions particularly to students with minimal background in data statistics or computer science.
2. Ability to initiate and manage programming and initiatives often with minimal supervision.
3. Ability to develop creative and practical higher education co-curricular programming such as workshops data-thons internships or service-learning opportunities.
4. Proficiency with some statistical software statistical data analysis or data management software or tools such as but not limited to Excel R SQL or Python.
5. Ability and desire for continuous improvement in pedagogy and understanding of data analysis management communications or ethics.
6. Demonstrated ability to interact well with diverse groups of people including students of different backgrounds (broadly defined) university leadership staff and faculty.
7. Excellent written and oral communication skills.

Preferred Qualifications

1. Applicants with experience in STEM public health or health sciences fields especially with a focus on education particularly in data science and data literacy.
2. Applicants with experience in AI broadly defined such as the technical aspects of AI using AI for research or other applications background in ethical use of AI the impact of AI on society or AI literacy.
3. Experience teaching a post-secondary course as an instructor.
4. Teaching experience in data-focused courses.
5. Applicants with training or education in teaching or pedagogy such as having taken courses or workshops.
6. Experience in running post-secondary co-curricular programming such as workshops internships and events.
7. Ability to develop industry or community relationships that lead to service-learning opportunities student internships or community partnerships.
8. A focus on engaging diverse populations (broadly defined) in data literacy.