An assistantship is awarded to a graduate student who provides teaching (teaching assistantship: TA) or research (research assistantship: RA) support to the University that is a part of his/her academic program. In recognition of this support, the tuition and a portion of health care (but not fees) are provided by the grant/contract funding agency or through the University.
To be appointed, to retain an appointment, or to be reappointed, a student must hold Regular (not Provisional) status, must maintain a cumulative average of at least B (3.00) in any course work taken, must be eligible to register (i.e., must not have more than three viable grades of Incomplete on his or her academic record), must be enrolled in a graduate degree program scheduled to extend through the entire period of the appointment or reappointment, and must be a full-time student.
Appointment Type and Duration
Effort devoted to the duties of a graduate assistantship typically range between 10 and 20 hours per week (also sometimes called a “half GA” and “full GA” respectively). Appointments ordinarily are made for the nine-month period, August 23 through May 22, but may be of shorter duration for a variety of reasons.
GA Payroll Deduction
Graduate Assistants are eligible to use payroll deduction as a method of paying university charges not covered by their tuition waiver. There is no additional cost for participating in the payroll deduction plan. Instructions on how to enroll in GA Payroll Deduction are available through the Bursar at this page.
Payroll, Benefits, and Health Insurance
Stipend rates for graduate assistants are graduated in terms of progress toward the advanced degree and experience.
- Level B/I: for graduate assistants with at least the baccalaureate.
- Level M/II: for experienced graduate assistants in a doctoral program with at least the master’s degree or its equivalent in the field of graduate study. Equivalency consists of thirty graduate level content course credits of appropriate course work beyond the baccalaureate completed at the University of Connecticut, together with admission to a doctoral program.
- Level P/III: for students with experience as graduate assistants who have at least the master’s degree or its equivalent and who have passed the doctoral general examination.
Graduate Assistants seeking employment beyond their GA appointment must complete the online Supplemental Employment Approval form, which requires their advisor’s approval and is submitted to The Graduate School for final approval.
Data Science Graduate Assistant
UConn Division of Enrollment Planning & Management and the Center for Excellence in Teaching and Learning are searching for a Graduate Assistant Data Scientist to join the ITS Data Science Team in several joint projects. The responsibilities will include the development of predictive models and the design/development of consuming reports, charts, and dashboards. The successful candidate will work closely with the Lead Data Scientist, and interact with ITS teams (Reporting and Analytics, Reporting Administration, Database Administration, Data Modeling/ETL), ITS partners, and others areas, as needed. The position is funded by the Center for Excellence in Teaching and Learning (CETL) and Division of Enrollment Planning & Management.
UConn Information Technology Services (ITS) is the University of Connecticut’s central IT department. ITS’s primary mission is to facilitate, coordinate and implement information technologies that enable the institutional missions of research, teaching, learning, and outreach. This is accomplished by identifying systems, services, and capabilities that have a positive, substantive impact on the community while delivering them robustly and at scale.
DUTIES AND RESPONSIBILITIES
Develop models using HPC and Cloud
Collaborate with Data Scientists in ITS Data Science team, WebFOCUS Administration team, WebFOCUS Reporting Analytics team, and other ITS teams, as needed
Interact with functional experts to gather requirements
Create reports, charts, and dashboards that consume models
Bachelor’s degree (or equivalent) in Data Analytics, Informatics, Data Science, Computer Science, MIS, Engineering, or Mathematics, and pursuing an MS or Ph.D degree in these areas.
Coursework should include some of the following: Machine Learning, Deep Learning, Data Mining, Applied Statistics, Data Structure & Algorithms, Big Data Analytics, Predictive Modeling. Machine Learning or Predictive Modeling is a must.
Proficient with Python programming, knowing R is a plus
Proficient in open source packages for machine learning and data processing, including TensorFlow, NumPy, pandas, scikit-learn, imblearn, Keras, Pandas, Matplotlib, altair, and packages for connections to data sources
Some experience with data exploration for data quality and fixes
Experience working with data reports and charts using reporting software
Experience working with relational databases (such as MySQL, Oracle, and MSSQL), SQL, and SQL clients (such as MySQL Workbench, SQL Developer, SSMS)
Experience with version control software such as Bitbucket, Git.
Master’s degree in Data Analytics, Business Analytics, Informatics, Data Science, Computer Science or Engineering and Mathematics (STEM) discipline.
Some experience with machine learning development. Experience could be course projects, internships, GA, or other experience.
Experience with a Cloud platform such as Azure, AWS, or GCP.
Experience with WebFocus (reports, charts, dashboards).
Resumes should be submitted to Cuong Do at email@example.com no later than August 31st.