PAY GRADE: 30S

CONTEXT OF THE JOB:

The Statistical Analyst works within the Office of Institutional Research and Effectiveness (IRE) to assist with the implementation, support, and expansion of the University’s business analytics capabilities. Under limited direction of the Director of Institutional Research, this position involves working with colleagues and users to organize administrative data, build statistical models, and pursue data cleaning initiatives related to the institutional platforms. The Statistical Analyst supports the development and implementation of a campus-wide business intelligence/decision support system directed at meeting the management and information needs of academic and administrative units across campus. The incumbent works on the design and optimization of data models and predictive models to support reporting and planning infrastructure at all levels of university. This functional role provides data management, design, and statistical analysis expertise in both developmental projects and day to day support of institutional information platform.

MAJOR RESPONSIBILITIES:

• Provide statistical support regarding enrollment management for the division related to student prospecting, admissions, enrollment, degree pathways, and student financial aid.
• Design and develop statistical analysis and predictive models and tools that will best meet the decision support needs of academic and administrative units across campus.
• Design and develop data models for ad-hoc query, drill-down, slice and dice capabilities, static reporting, managed queries, and dashboards.
• Work with business end users to understand their business processes, gather and document project requirements and translate them into functional and non-functional specifications.
• Provide support and expertise on the creation, development, modification, testing and documentation of data models.  Ensure that the data is accurate and consistent with University-wide reporting standards.
• Collaborate with other colleagues in IRE to standardize reporting implementation across a variety of contexts for standard production and non-standard ad-hoc University reports. 
• Work with the Extract/Translate/Load (ETL) team in IT to develop, implement and document data validation procedures.
• Respond to ad hoc requests/analysis for information from deans, associate deans, senior academic administrators, department chairs and faculty across campus. 
• Perform other job-related duties as assigned.

QUALIFICATIONS:

• Bachelor’s degree in statistics, information technology, or other related discipline with evidence of the application of quantitative research methods using administrative data and two years of experience or an equivalent combination of education and experience.
• Willingness to learn and develop solutions in new technologies and implement solutions that reflect the state of the industry.
• Knowledge of statistical predictive models and ability to implement modeling tool applications for institutional planning. 
• Demonstrable record of experience and success in using statically software such as, SAS, SPSS, R, Python, and JMP.
• Demonstrable record of experience and success in using SQL based data management tool such as Data Grip or Coginiti Pro.
• Proficient in handling database and statistical analysis technology.
• Ability to work with minimal supervision, define tasks, and follow through is essential, as is the ability to fully document in writing all developmental activity related to information reporting.
• Strong analytical and logical thinking skills.
• Ability to work independently. Strong interpersonal skills, as well as excellent oral and written communication skills are critical. 
• Ability to interact effectively with senior academic and administrative leaders, with department chairs and faculty, and with a broad spectrum of professional and salaried staff.
• Must be an effective listener, able to distill complex data and information requirements from a wide range of requesters into responsive data and information products.