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Data Science and Predictive Analytics Part Time Instructor

Recruitment Period

Open date: February 22nd, 2019
Last review date: Friday, Mar 8, 2019 at 11:59pm (Pacific Time)
Applications received after this date will be reviewed by the search committee if the position has not yet been filled.
Final date: Tuesday, Dec 31, 2019 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.


In-person teaching positions are now available in the Data Science & Predictive Analytics for Business Professionals Program. Most courses will be offered on campus in Irvine, CA. We are seeking qualified applicants possessing current knowledge and teaching experience in all aspects of Predictive Analytics and Data Science including: Defining Business Goals, Data Preparation, Modeling, Verification, Model Deployment/Refinement, and Data Visualization.

Our curriculum is constantly updated and tailored to bring students the background, expertise, and business practices to remain competitive and advance their careers. Taught by qualified practitioners, our courses feature practical applications, underlying rationale, and current issues, all of which can be immediately utilized in and applied to our students’ work environments.

Part-time, temporary assignments are on an "as needed" basis. This is an ONGOING recruitment.


Basic Qualifications
Advanced degree from an accredited institution

Additional Qualifications
Current knowledge of, demonstrated proficiency in, and practical application of the data science and predictive analytics subject area
Must be committed to the highest level of academic standards and integrity
Highly effective oral and written communication skills, including the ability to convey conceptual and complex ideas and information
Highly effective interpersonal skills
Proficiency in (or willingness to learn) the use of instructional technology and online teaching tools
Experience with Python, SQL, Java, or JavaScript is preferred
Current participation in professional associations
Comfort in dealing with international professionals and students

Preferred Qualifications
Experience designing/revising curriculum and measuring student performance
College-level teaching experience (or the corporate equivalent)

Course Descriptions: Predictive Analytics and Data Science Course Instructor (additional courses may be added as appropriate)

Applications of Predictive Analytics
This intensive hands-on course gives you the skills necessary to extract stored data elements, understand what they mean in the company, transform their formats, and derive new relationships among them to produce a data-set suitable for analytical modeling. Use these skills to produce a fully processed data set, compatible for building powerful predictive models that can be deployed to increase profitability in your company.

Strategic Business Analysis using Predictive Analytics
Learn to use analytic insights to seek out increasingly small margins and understand your customers, products, channels, partners and more. This course provides a framework to identify which decisions will be improved, and how, so that you can build business support for predictive analytic efforts, scope them appropriately, and develop a plan for successful implementation. Understand the process behind decision management, a proven approach to linking predictive analytics to your business and its goals.

Data Preparation for Data Mining
This hands-on course teaches the skills necessary to extract stored data elements, understand what they mean, transform their formats, and derive new relationships among them in order to produce a dataset suitable for analytical modeling. Data preparation for data mining consists of three elements: (1) Data Mining Process delineation (you have to understand the overall process), (2) Data Understanding (you can’t properly prepare data until you understand it), (3) Data Pre-processing (transforming data into a form compatible with data mining.) By the end of the course, you will be able to use these skills to produce a fully processed data set, compatible for building powerful predictive models that can be deployed to increase profitability for your company.

Modeling Methods, Deploying, and Refining Predictive Models
Learn how to use the basics of predictive analytics and modeling data to determine which algorithms to employ. Learn “best practices” and the influence various options have on predictive models to gain a deeper understanding of how the algorithms work qualitatively. Understand common approaches to deployment of predictive models and be able to integrate models into decision-making processes. Learn how to monitor models, when to update them, how to deploy and refine them, and to develop applicable performance metrics.

Business Applications of Data Science
Highly successful businesses know that the rules have changed. No longer can they rely solely on their product or service to grow; they must leverage their data (financial, customer support, web interactions, etc.) to better understand their customers and learn from the collective experiences of their organizations to remain competitive. This course provides individuals the skills needed to effectively collect and manage Big Data and perform data-driven discovery and prediction, extracting value and competitive intelligence for their organizations.

Data Exploration, Analytics, and Visualization
The world produces more than 2.5 exabytes of data every day. Visualization is one key approach to gaining insight from this mountain of data, enabling you to see trends and patterns (along with gaps and outliers) in the data that are not easily identified in rows and columns of numbers. Visualization can also provide access to huge data sets, such as weather, web traffic, sales and voting records. Data sets of this size have the potential to be overwhelming and inaccessible; a good visualization provides a way to explore, understand, and communicate the data, along with actions the data indicate should be taken. You will use Tableau in conjunction with Alpine to explore and analyze data and learn how it can be used to visualize Big Data.

Big Data Visualization and Analytics
This course will begin with a review of some case histories of Big Data use. Basic elements of successful Big Data implementation will be covered as well as a review of commercially available tools and technology. A focus will be placed on value opportunities in online marketing, search optimization and site performance modeling.

Technology Programs unit offers more than 200 professional courses in eighteen (18) certificate programs to over 3,550 students each year. Our students are largely newly graduated professionals and adult professionals working in full time positions who are seeking additional education that will enable them to update their skills, change careers, or prepare for industry certifications or exams. Our programs are designed to meet the needs of these business professionals at all levels of their careers, providing them with flexible enrollment options to initiate their professional development at any time throughout the year, without an application. As a result of our commitment to academic excellence, professionals can acquire the skills and knowledge they need to face a world of continual change. We are seeking world-class instructors who are experts in their fields, with extensive hands-on experience as business professionals and community leaders. Applications to teach are accepted on a rolling basis throughout the year to both fill immediate program needs, and to increase the depth of the instructor pool for future needs.

To apply for this position, please click this link:

Individuals hired to teach these courses must understand that all such agreements with the University are made on a course-by-course basis and that the Instructor will be made no guarantee of continual involvement with the University in any capacity.

The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.

Job location

Irvine, CA


Document requirements
  • Curriculum Vitae - Your most recently updated C.V.

  • Cover Letter

Reference requirements
  • 3 required (contact information only)