UNT System Overview:
Welcome to the University of North Texas System, or UNT World as we like to call ourselves. UNT World includes the University of North Texas in Denton, the University of North Texas at Dallas and the University of North Texas Health Science Center in Fort Worth. We are the only university system based exclusively in the robust Dallas-Fort Worth region and we are committed to transforming lives and creating economic opportunity through education. Over the past decade, combined UNTS enrollment has grown by more than 25 percent to nearly 44,000 students.Posting Title:
UNT-Inst Rsrch & Effectiveness-110110Job Location:
DentonFull Time/Part Time:
Commensurate with experienceDepartment 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.
- 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.
Monday – Friday, 8 am – 5 pmDriving University Vehicle:
This is a security sensitive position.EEO Statement:
The University of North Texas System and its component institutions are committed to equal opportunity and comply with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University of North Texas System and its component institutions do not discriminate on the basis of race, color, sex, sexual orientation, gender identity, gender expression, religion, national origin, age, disability, genetic information, or veteran status in its application and admission processes, educational programs and activities, and employment practices.Classification Title:
Data ScientistPhysical Requirements:
Carrying, Lifting up to 10 pounds, Pulling , Pushing, Reaching, Sitting, Standing, Twisting, Walking, Writing, Grasp, Talk or Hearo:
Works with C-Suite leaders, senior administrators, Deans, staff, external constituents, and internal DAIR colleagues to formulate and scope questions to assist leaders in higher education transformation.o:
Develops predictive models to help leaders solve critical higher education problems.o:
Influences a general audience to understand the quality, completeness, and appropriate use of data science approaches and provides advice about choice of statistical and machine learning approaches.o:
Develops tools and libraries to create efficiencies for future work.o:
Working in partnership across the DAIR office, identifies new sources of data within the UNT data landscape that will improve information about student and administrative outcomes.o:
Stay at the forefront of emerging analytics and data science issues in higher education by actively representing the University at conferences or meetings.Posting Number:
S1306PSpecial Instructions to Applicants:
*Applicants must submit a resume and a cover letter with their online application.
- Applicants should attach a one page maximum executive summary to “Other Document” on the “Attach Documents” screen, outlining a strategic problem/question they were asked to solve, what data sources were used, what data science approaches were used, what data quality steps were undertaken, and what findings were surfaced. Applicants should conclude with a brief summary of how the organization leveraged the work to respond to the original problem/question.