Department Summary
The Data, Analytics, and Institutional Research (DAIR) team is made up of professionals with a wide range of experience in higher education settings. Our team has professional credentials and degrees geared towards helping the institution improve through data informed decision making. The team is responsible for a wide-array of projects.
The mission of the DAIR team is to promote sound analytic and institutional research practices, manage existing and develop new data models, and provide decision makers and external agencies with official and transactional academic, enrollment, faculty, financial, and student data.
Working in partnership across the institution, DAIR is tasked with supporting analytic deployment via the Insights program, surfacing data to assist with institutional planning and policymaking, and responding to other strategic data requests in accordance with the UNT mission and goals. DAIR promotes a culture where employees across the institution have the data training and tools they need to best respond to pressing institutional concerns.
DAIR was recognized in 2019 as a recipient of a CIO 100 award for innovation and one of only three recipients from Higher Education. DAIR staff frequently contribute to the national conversation on analytics and the unit takes professional development seriously. Employees within the unit also have access to a generous tuition benefit program.
Position Overview
This position is responsible for partnering with a variety of internal and external stakeholders to perform advanced data design and analysis using a broad array of data sets to create new knowledge useful to the university. This position proactively identifies, develops, and implements analytical and institutional research studies to find creative solutions to medium to long term issues facing the university. Leverages programming, analytics and statistical processing tools to respond to requests for data, completes local, regional, and national surveys to impact institutional reputation and standing. Applies expert statistical methodologies to educational and administrative outcomes.
Minimum Qualifications
Master’s Degree in quantitative disciplines such as Business Administration, Public Policy, Statistics, Educational Measurement, Higher Education, or a related discipline, and three years of professional experience.
Knowledge, Skills and Abilities
- Experience in using SPSS or SAS or other comparable statistical analysis program such as R; Knowledge of programming in SAS, SPSS, and SQL.
- Knowledge of data analysis and research design methodologies.
- Capacity for independent and creative thinking and writing on research and statistical problems.
- Ability to work with data from multiple sources.
- Knowledge of business intelligence and reporting tools such as SAS VA, SAS VS, Tableau, WebFOCUS, Cognos or OBIEE.
- Excellent analytical and quantitative skills.
- Excellent communication skills, both verbal and written.
- Stays at the forefront of emerging analytics and institutional research issues in higher education.
Preferred Qualifications
Master’s Degree in quantitative disciplines such as Analytics, Business Intelligence, Data Sciences, Business Administration, Computer Science, Public Policy, Statistics or a related discipline. Three years of professional experience.
The following knowledge, skills, and abilities are required:
Experience with at least one of the programming languages/Tools : R, Python, SQL, MYSQL, BigQuery, or PostgreSQL
Technical expertise regarding data models, database design development, data mining and segmentation techniques.
Ability to develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.
Proactively identifies, analyzes and interprets trends and patterns in complex data sets.
Experience processing, filtering and presenting large quantities of data.
Skills in data mining, model building and other analytical techniques to identify business opportunities.
Knowledge of data analysis and research design methodologies.
Capacity for independent and creative thinking and writing on research and statistical problems.
Ability to work with data from multiple sources and varying degrees of quality.
Knowledge of business intelligence and reporting tools such as SAS Viya, SAS Visual Analytics, SAS Visual Statistics, Tableau, or Microsoft BI.
Excellent analytical and quantitative skills.
Excellent communication skills, both verbal and written.
Proficient knowledge of the function/discipline and demonstrated application of knowledge, skills and abilities towards work products required.
Background in a variety modeling techniques: GBM, logistic regression, clustering, neural networks, NLP.
Other Preferred Qualifications:
Two years of related experience in a higher education institutional research or business intelligence capacity.
Working knowledge of ERP such as PeopleSoft, SAP or Banner.
Familiarity with machine learning frameworks, like TensorFlow or PyTorch.
Experience in machine learning/deep learning-based algorithms with structured/unstructured data.
Experience with mathematical & statistical understanding behind the algorithms.
Experience with converting & writing distributed algorithms to process large amount of unstructured data.
Doctoral Degree in quantitative discipline noted above.
