Assistant Teaching Professor of Database and Data Science
Carnegie Mellon University: Heinz College
Location: Pittsburgh, PA
Open Date: Dec 7, 2021
CMU is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.
The Heinz College of Information Systems and Public Policy at Carnegie Mellon University is seeking qualified candidates for the open position of Assistant Teaching Professor of Database and Data Science. We invite academics or professionals with experience applying modern data analytics techniques to real world problems. This full-time, teaching-track position is a unique opportunity to join one of the most respected research universities in the world. The Heinz College offers a collegial and intellectually stimulating environment at the intersection of people, policy, and technology. We are looking for an individual committed to instilling analytical and evidence-based practices to our undergraduate and graduate students at Heinz College and across Carnegie Mellon University.
We prepare students to understand and leverage technology responsibly to effect change in business and society. We train our students to collect and analyze data in pursuit of positive transformation. We teach a set of data governance and analytical skills with a focus on the effectiveness, equity, and integrity in the decision process and its ramifications. Armed with this unique set of skills, Heinz College graduates are in great demand across all sectors of the economy.
Heinz College adheres to four basic principles of being grounded in real-world problem solving; staying ahead of the curve in innovation; nurturing diversity; and developing compassionate leaders. The College, since its founding in 1968 as the School of Urban and Public Affairs, has had a long history of commitment to diversity, equity, and inclusion, made ever more relevant in today’s world of technology-driven social change.
The role of Assistant Teaching Professor of Database and Data Science is essential in preparing our students to lead through intelligent decision making and action. This position will be responsible for developing and delivering classes that prepare Heinz students in database and data analytic methods.
We are in search of a colleague who is excited about teaching and helping students learn. Specific job responsibilities include developing, preparing, and teaching Introductory and advanced-level undergraduate and graduate courses in database systems, data management, and data analytics.
We are specifically interested in candidates with expertise in traditional and emerging database systems and at least one field in data science, such as big data technologies and algorithms, applied machine learning, visualizing and communicating data, large scale and unstructured data analytics, cloud computing, and/or data-driven modeling and prediction. In addition, we are seeking a candidate who reaffirms our values of diversity, equity and inclusion, and who exemplifies that in their teaching, research, and interactions with colleagues, students, and staff.
The desired set of skills include:
- Ability to develop and deliver relevant coursework in Database Management, Structured Query Language (SQL), Data Governance, NoSQL, Cloud Databases, and elements of the Data Analysis Pipeline
- A strong understanding of relational and non-relational data modeling concepts including experience with unstructured and dynamic data.
- Experience in integrating heterogeneous data sets including data acquisition, cleaning, and staging. A clear understanding of ETLs and their applications.
- Ability to conceptualize, structure, and oversee analytics projects
- Culturally responsive interpersonal and communication skills
- Demonstrated commitment to diversity, equity, and inclusion
- Background in teaching or working in/with academia highly preferred
The Teaching Track at Carnegie Mellon is a career-oriented, non-tenure, faculty track with renewable fixed terms and opportunities for promotion from Assistant to Full Teaching Professor. Faculty on the teaching track at Heinz College are expected to teach an effective teaching load of 72 units, the equivalent of six full-semester length classes or twelve half-semester length classes (minis) per academic year. This position emphasizes teaching, student advising, curriculum development, and supervising collaborative projects. Teaching Track faculty serve on committees alongside other faculty at the College and University levels. The Track is ideal for candidates who love to teach and mentor students. This position has a fall 2022 anticipated start date.
We welcome applicants with a Ph.D. in Computer Science, Information Systems, or a closely related field as those who have built their experience in industry or professional careers. “ABD” candidates nearing completion of their degrees may be considered. Willingness to work collaboratively with faculty and to mentor students from a wide range of disciplines, cultures and academic backgrounds is essential.
A complete application packet will include the following: cover letter; Curriculum Vitae; a statement of teaching philosophy; a diversity statement; contact information for three or more references; and any additional supporting documentation which may include evidence of teaching effectiveness and/or representative of scholarly work.
Equal Employment Opportunity Statement
Carnegie Mellon University shall abide by the requirements of 41 CFR §§ 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, or national origin. Moreover, these regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, national origin, protected veteran status or disability.