Professor of Practice in Data

The Connolly Alexander Institute for Data Science (CAIDS) at Tulane University seeks a Professor of Practice in Data to teach introductory and multi-disciplinary courses in data literacy, data visualization, presentation, management, and/or analysis. CAIDS promotes, teaches, and supports data literacy and data science for students, faculty, and the broader community through courses, workshops, events, student internship, seed grants, statistical consulting, and supporting interdisciplinary research groups.

This is a full-time, non-tenure-track position eligible for promotion to Senior Professor of Practice. The initial appointment is renewed every three years and later up to five or seven years. Renewal is based on an evaluation of teaching, service, and research. Professors of Practice are eligible to be considered for promotion to Senior Professor of Practice after at least three years. For more information on CAIDS, visit .

Required Application Materials

Interested candidates should submit the following materials:

• Cover Letter
• Curriculum Vitae (CV)
• Teaching statement/philosophy (upload to the Miscellaneous Documment section)

The cover letter and/or teaching statement should address the candidate’s interest and experience in teaching introductory and intermediate courses on data literacy, data analysis, or data management to a diverse student body, especially students with minimal background in data, statistics, or computer science. Additional documents may be requested at a later date.

Teaching

• This position has a 2/2 teaching load (two courses per semester) to accommodate service work. The Professor of Practice will be expected to teach:
  • DATA 1010: Introduction to Data, a course that introduces students to fundamental skills in data literacy, analysis, communication, and ethics.
  • DATA 2030: Data Visualization, a course surveying creative and analytical theories and techniques for understanding and developing data visualizations, including graphs, charts, maps and interactive tools such as dashboards.
  • At least one multi-disciplinary undergraduate course in their area of interest or expertise. We are particularly interested in candidates who can add new courses to our existing curriculum including, but not limited to, analysis of image, audio, and other non-standard data types; survey and polling design and analysis; biostatistics, bioinformatics, or analysis of clinical trial/experimental data, and courses that could fit into the AI Literacy Minor. All CAIDS courses draw from multi-disciplinary perspectives and are open to students of all backgrounds and abilities, usually without a prerequisite.

Service

• In addition to teaching, the Professor of Practice will develop and facilitate CAIDS programs and services that increase faculty and student participation in data-related research while upholding CAIDS’s mission of being inclusive to all data fields. Based on the candidate’s expertise, possible service roles may include:
  • developing and coordinating internal and external internship and research-assistant programs;
  • facilitating collaborative grant applications;
  • providing statistical, data, or applied-AI consulting services;
  • coordinating research-related programming such as seminars, workshops, data-thons, and poster sessions; and
  • supporting interdisciplinary research groups in the Professor of Practice’s areas of expertise or interest.
• This position will also support data visualization co-curricular activities. Responsibilities include working closely with librarians at Howard-Tilton Memorial Library to plan the Love Data Week Data Visualization and Physicalization competitions and exhibits, promoting and coordinating student participation in
• Tulane poster sessions, developing and facilitating occasional data visualization workshops, and undertaking related service activities.
  The Professor of Practice will contribute to shaping CAIDS’s priorities and future direction, serving as an active partner in managing the institute’s programs and initiatives.

Research

Conducting research is not a requirement, but data-related research or scholarship on data science teaching and learning can be incorporated into the workload.

Required Education and Experience

• A Ph.D. in a data-related field* and teaching experience as an instructor or teaching experience in a data-focused course; OR
• A Master’s degree in a data-related field,* with at least five (5) years of combined experience teaching in post-secondary or secondary education and/or working in industry or government in a data literacy, data analysis, or data management position.
  • *Data-related fields include, but are not limited to, statistics (preferably applied), quantitative social sciences (e.g., economics, sociology, political science, psychology, public or business administration), humanities with a data focus, public health, education with a data focus, and numerous STEM fields such as Engineering, Computer Science, Natural Sciences, etc. Applicants with a background in qualitative research methodology will also be considered if 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

• Demonstrated ability to teach in post-secondary institutions, particularly to students with minimal background in data, statistics, or computer science.
• Ability to initiate and manage programming and initiatives with minimal supervision.
• Ability to teach Introduction to Data and Data Visualization.
• Ability to develop practical and creative post-secondary education programming and services that promote faculty and student engagement in data-related research.
• Experience developing data visualizations, including graphs, charts, and interactive tools such as dashboards, using applications such as Excel, PowerBI, Flourish, Tableau, or R.
• Commitment to continuous improvement in pedagogy and data science.
• Demonstrated commitment to engaging diverse populations in data literacy.
• Demonstrated ability to interact well with diverse groups of people, including students from varied backgrounds, university leadership, staff, and faculty from different disciplines.
• Excellent written and oral communication skills.

Preferred Qualifications

• Experience teaching data-focused post-secondary course(s) as the instructor of record.
• Training or education in teaching or pedagogy.
• Experience developing or managing post-secondary programming such as workshops, internships, events, and research services.
• Ability to provide data, statistical, computer science, or applied AI consulting services to faculty.
• Ability to develop industry or community relationships that lead to service-learning opportunities, student internships, community partnerships, or external grant proposals.
• Ability to engage with students in data storytelling methods through data visualization.
• Willingness to cover and engage with data visualization theories and methods using both scientific and creative techniques.
• Ability and desire to learn and teach multiple data visualization theories or methodologies across multiple fields including arts, humanities, social sciences, liberal arts, public health, and STEM.