star twitter facebook envelope linkedin instagram youtube alert-red alert home left-quote chevron hamburger minus plus search triangle x

Now Hiring: Assistant Teaching Professor of Database and Data Science

faculty headshots

Our faculty are among the best in the world, and Heinz College provides a place for faculty - and students - committed to innovation, collaboration, and intelligent action.

Carnegie Mellon University: Heinz College

Location: Pittsburgh, PA
Open Date: Mar 25, 2022

Application Process

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.

Apply Now

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.

Students attend a presentation of Data Science for Social Good

The Heinz College community gathers regularly for faculty town halls, faculty-staff meetings, the Heinz Informal Lecture Series, and more.


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.
Students attend a presentation by Data Science for Social Good Fellows.

Community support for faculty includes opportunities to engage with colleagues through regular meetings, research seminars, and "lunch and learn" events,


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.

Application Instructions

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.

Community Support

Some unique characteristics of Heinz College are authentic collaboration, faculty camaraderie, and community support. Our research programs are best described as data-intensive social science. Our economists, statisticians, operations researchers, computer scientists, and management experts sit side by side, collaborating constantly and not sitting in traditional departmental silos. For this reason, they are able to approach complex societal problems in an altogether different way.

Some formal ways we offer faculty a supportive community include the Heinz Informal Lecture Series (HILS), Research Seminars, Lunch & Learn events, regular faculty/staff events and Town Hall meetings, and much more. Impromptu hallway conversations, shared meals, and social gatherings are frequent informal ways our faculty engage across disciplines. We encourage you to ask questions and see for yourself when you visit campus.

  • Faculty and Research

     Our faculty researching in the areas of database and data science include:

    Leman Akoglu Leman Akoglu, Dean's Associate Professor of Information Systems 
    Leman's research interests span a wide range of data mining and machine learning topics with a focus on algorithmic problems arising in graph mining, pattern discovery, social and information networks, and especially anomaly mining; outlier, fraud, and event detection. At Heinz, she directs the Data Analytics Techniques Algorithms (DATA) Lab.  



    David Choi David Choi, Assistant Professor of Statistics and Information Systems
    David's research focuses on statistics and machine learning for network data, including exploratory data analysis and community detection, other network models involving latent variables or unsupervised learning, and causal inference in the presence of social network effects.


    Rayid Ghani Rayid Ghani, Distinguished Career Professor 
    Rayid works with governments and non-profits in policy areas such as health, criminal justice, education, public safety, economic development, and urban infrastructure. Rayid is also passionate about teaching practical data science and started the Data Science for Social Good Fellowship that trains computer scientists, statisticians, and social scientists from around the world to work on data science problems with social impact.  

    Gabriela Gongora-Svartzman Gabriela Gongora-Svartzman, Assistant Teaching Professor of Information Systems
    Gabriela’s research is focused towards bridging the quality of experience and quality of services in smart cities. Gabriela has a multidisciplinary approach to solving real world problems, through data visualization, data analytics and data-driven support systems for decision-making. Her three main research areas are 1) Urban Informatics, 2) Data Visualization for Decision Making and 3) Resilience and Social Perception.


    Ramayya Krishnan Ramayya Krishnan, Dean, Heinz College of Information Systems and Public Policy; William W. and Ruth F. Cooper Professor of Management Science and Information Systems
    Krishnan is an expert on digital transformation and has worked extensively with firms and policy makers on using technology and analytics to achieve policy goals. He has made seminal contributions to technology management and policy. His current research interests are in the responsible use of AI and in data-driven approaches to support workforce development. 

    Rahul TelangRahul Telang, Trustees Professor of Information Systems; PhD Program Chair
    Rahul's research research interest lies in two major domains. First is on Digital Media Industry with a particular focus on digitization of songs, movies, TV and books is affecting the incentives of content provider, content distributors as well public policy challenges in terms of innovation and copyright. His second area of work is on economics of information security and privacy.

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.