University of Utah Data Mining Analyst - Student Intern in Salt Lake City, Utah
Open Date 10/11/2018
Requisition Number PRN08613N
Job Title UU Student - Computer
Working Title Data Mining Analyst - Student Intern
Job Grade SJ
FLSA Code Nonexempt
Patient Sensitive Job Code?
Type Non Benefited Staff / Student
Standard Hours per Week 19
Full Time or Part Time? Part Time
Work Schedule Summary
M-F, hours to be arranged.
Is this a work study job? No
VP Area President
Department 00417 - UIT - ACS
City Salt Lake City, UT
Type of Recruitment External Posting
Pay Rate Range $12.00/yr.
We seek highly motivated students to help support the University Support Services group within the University Information Technology department. This opportunity will focus on Data Mining and Predictive Analytics. Students at this level work under the direction ofUSSstaff. The position provides support primarily to end users by conducting data mining and machine learning activities using various data management tools and applications. Candidates should be well versed in the application of data mining algorithms on various data types and should possess the ability to apply that knowledge in the context of predictive modeling and machine learning.
AboutUIT: University Information Technology (UIT), the central IT service provider for campus, reports to the Chief Information Officer and is responsible for many of the University of Utah’s most critical common IT resources including the campus network; the Campus Information Services (CIS) portal; UMail, telephone, and online collaboration services; high performance and research computing; information security; teaching and learning technologies; software licensing; and a host of other systems and services. For more information aboutUITvisit http://www.it.utah.edu.
About the University: Located in Salt Lake City, in the foothills of the Wasatch Mountains, the University of Utah is the flagship institution of the State of Utah’s system of higher education and a member of thePAC-12 Conference. Salt Lake City combines the amenities of a major metropolitan area of more than one million people with the friendliness and ease of living of a small, Western city. Seven major ski resorts are within an hour’s drive from campus, and opportunities to pursue activities from biking to hiking to fishing abound. Salt Lake is also home to the Utah Symphony and Opera, the Utah Ballet, several professional sports teams, and a wide range of other cultural and recreational activities. http://www.employment.utah.edu/staff/work.php
The incumbent will work on various technical activities such as documentation, data analysis and visualization, data mining, and predictive model development. The incumbent must also assist in championing the use of a coherent development framework, such asKDD, for data selection, pre-processing, transformation, and mining in addition to model selection, interpretation, and performance outputs.
Must be a current University of Utah Student.
Preference will be given to students with related technical coursework and/or professional experience.
Candidates will be expected to have advanced knowledge of high-dimensional, multivariate statistical analysis techniques and understand how to develop, train, and test various supervised and unsupervised learners including: classification and association algorithms, time series and regression models, and clustering and feature selection algorithms. Knowledge of ensemble learning techniques, approaches to model selection and performance measurement, and residual analysis are required. Knowledge of Oracle, Cloudera (Apache Hadoop and related projects), Spark APIs, and Docker/Kubernetes deployments are big pluses. Project management, relational database analysis, and advanced relevant programming skills (i.e., R, Python,SQL, etc.) are a plus. Knowledge of mathematical optimization using Python or Matlab are a plus. Candidates must possess appropriate computer skills, excellent written and verbal communication skills, and a high level of interest and initiative in learning new technologies. Successful candidate must have a positive attitude and focus on solving issues.
Special Instructions Summary
The University of Utah is an Affirmative Action/Equal Opportunity employer and is committed to diversity in its workforce. In compliance with applicable federal and state laws, University of Utah policy of equal employment opportunity prohibits discrimination on the basis of race or ethnicity, religion, color, national origin, sex, age, sexual orientation, gender identity/expression, veteran’s status, status as a qualified person with a disability, or genetic information. Individuals from historically underrepresented groups, such as minorities, women, qualified persons with disabilities, and protected veterans are strongly encouraged to apply. Veterans’ preference is extended to applicants, consistent with University policy and Utah state law. To inquire about this posting, email: email@example.com or call 801-581-2300. Reasonable accommodations in the application process will be provided to qualified individuals with disabilities. To request an accommodation or for further information about University AA/EO policies, please contact the Office of Equal Opportunity and Affirmative Action, 201 S. Presidents Cr., Rm 135, (801) 581-8365 (V/ TDD ), email: firstname.lastname@example.org .
The University is a participating employer with Utah Retirement Systems (“URS”). Individuals who previously retired and are receiving monthly retirement benefits from URS must notify the Benefits Department upon hire. Please contact Utah Retirement Systems at (801) 366-7770 or (800) 695-4877 or the University’s Benefits Department at (801) 581-7447.
This position may require the successful completion of a criminal background check and/or drug screen.