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Lecturer I/II -Mgmt Science & Statistics
Category: Other
  • Your pay will be discussed at your interview

Job code: lhw-e0-89769612

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University of Texas at San Antonio

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  Job posted:   Thu May 17, 2018
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Lecturer I/II -Mgmt Science & Statistics
Position Information

Title of Position
Lecturer I/II -Mgmt Science & Statistics

Requisition Number

Department Posting Name
Management Science & Statistics

Main Campus

Recruitment Type

Position Type
This is a Non-Tenure Track Faculty, non-benefits eligible position

Grant Funded?

Hours per week
Varies-based on assigned classes

If employee will be working a schedule other than Monday - Friday, 8:00am - 5:00pm, specify hours and days to be worked

Schedule varies-dependent upon class schedule and assigned classes.

If Temporary, Ending Date

Recruiting Rate
$5,000-6,000 (per course)

Beginning Salary Flexibility

Pay Basis

Required Education
Master's Degree

Do you want to allow additional experience to substitute for required education?

Preferred Education
Doctoral Degree

Field of Study

Data analytics, applied statistics, machine learning, management science, operations research, data science, or a closely related field

MS Office Experience Required
Word, Excel

Will this position require driving a UT or personally owned vehicle?

Other Computer and Software Skills Required

Statistical Software such as SAS, SPSS, R, Microsoft Excel, etc.

Experience and Other Skills Required

Lecturer I: University teaching/tutoring or corporate training experience

Lecturer II: A minimum of two years teaching experience at UTSA or commensurate experience at another institution (in the subject in which classes will be assigned) and demonstrated high levels of performance as indicated by formal review.

Do you want to allow additional education to substitute for required experience?

Other Skills Preferred

Preference will be given to candidates with relevant work experience, and or teaching experience.

Description of Job Duties

Teaching courses in the M.S. of Data Analytics Program. Specifically in one of the following three courses:
1. DA 6213. Data-Driven Decision Making and Design (3-0) 3 Credit Hours.
This course familiarizes students with basic scientific processes and formalisms, such as question formulation and hypothesis development. Students will be provided the opportunity to gain an understanding of how formulated questions and hypotheses can lead to data collection and analysis, as well as how data itself can be explored and summarized to generate such questions and hypotheses. The course also introduces students to foundational data analytics processes, such as the data-to-decision processes, data handling processes, and data analysis processes. Data provenance for data-to-decision traceability and critical scientific documentation principles important to scientific and analytic functions is also discussed.
2. DA 6223. Data Analytics Tools and Techniques. (3-0) 3 Credit Hours.
Students will be provided the opportunity to gain education and experience with common tools and techniques used in a variety of data analytics application areas. Students will become familiar with database technology and leading commercial and open source analytics platforms. Students will also be provided the opportunity to learn how to use these technologies and platforms to solve data analytics problems by obtaining a basic understanding of database querying and basic scripting in analytics platforms. Students will not become scientific programmers from this course, nor will they learn the formalisms of programming per se; rather, they will be provided the opportunity to learn and experience how to develop functional scripts and leverage existing analytics libraries to solve data analytics problems using software.
3. DA 6813. Data Analytics Applications. (3-0) 3 Credit Hours.
Students will be presented a big picture understanding of data analytics, including its purpose, common benefits and challenges, important analytic processes, and what is needed to perform data analytics, such as skills, tools, technology, etc. Students will be introduced to a wide variety of data analytics applications in a wide variety of fields, such as information technology, cyber security, bioinformatics, biomedical/health, insurance and risk, finance, economics, accounting, business intelligence, crime and fraud detection, marking and customer analytics, energy and environmental, manufacturing and operations, and logistics and supply chain. Data analytics applications will be demonstrated through case-based study and guest lectures from data analytics experts and managers in the various application areas listed above.

Posting Open Date

Posting Close Date at midnight on

Open Until Filled

Special Notes To Applicants

Note 1: Hiring Summer 2018; teaching graduate courses in Data Analytics

Note 2: At the discretion of the hiring manager/department, this position may be classified as a Level I or Level II depending on the qualifications of the finalist candidate.

Note 3: UTSA is a tobacco-free campus.

Note 4: UTSA is an Equal Employment Opportunity/Affirmative Action Employer. Minorities, women, veterans, and individuals with disabilities are encouraged to apply.

Note 5: This is a security sensitive position. Employment is contingent upon a successful background check.

Note 6: At the discretion of the hiring department, this position posting may be closed once a sufficient number of qualified applications has been received.

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