Data Management Analyst II

  • University of Florida
  • United States
  • Mar 23, 2022
Technology Full Time - Continuing

Job Description:

Classification Title:

Data Management Analyst II

Job Description:

Consulting with students, staff, and faculty on:

  • Data analysis questions, both statistical and mathematical
  • Best practices for data representation
  • Data storage, formatting, and querying
  • Computer programing
  • Design of experiments
  • Developing experimental protocol, including survey instruments.

Implementing and running data analysis, formatting output, explaining analysis approaches, and interpreting analysis results

Assisting clients with the creation of publication-ready tables and graphs, and other work associated with the process of project reporting and publication.

Researching new software solutions, such as R-packages, SAS PROCs or SAS MACROS that might be useful to SCU clients

Assisting with teaching and developing examples for practical data analysis in applied statistics courses and/ short courses.

Developing and maintaining a blog to answer common statistical questions that have arisen in consulting sessions.

Instructions and/or discussion on appropriate methods for data analysis are provided. Instructions on workload priorities are given.

Follows established statistical procedures and may recommend new approaches to data analysis. Developing additional procedures as needed.

Develops training material and workshops to enhance statistical knowledge of IFAS personnel.

Contact will be limited to IFAS faculty, graduate students, and staff.

No data information obtained from clients to be disclosed without permission.

Monday to Friday, 8AM to 5PM

Expected Salary:

$51,500 - $66,900

Minimum Qualifications:Master’s degree in an appropriate area; or a bachelor’s degree in an appropriate area and two years of relevant experience.
Preferred Qualifications:

Proficiency in R and a good working knowledge of one other statistical software such as SAS, JMP, Stata or SPSS. R coding skills include Data Carpentry techniques, Linear Mixed Models, Generalized Linear Mixed Models, Non-linear Mixed Models and Bayesian Analysis.

Special Instructions to Applicants:

Application must be submitted by 11:55 p.m. (ET) of the posting end date.

Health Assessment Required:No