• Econometrics Summer 2019 Fellowship (PhD)

    Job Locations US-NC-Cary
    Requisition ID
    Visa Sponsorship
    Travel Requirements
  • Overview

    Germany SAS


    Econometrics Summer Fellowship 2019

     The Econometrics and Time Series software development division at SAS is pleased to announce SAS Summer Fellowship in Econometrics for the summer of 2019. Open to doctoral candidates in economics, statistics, finance and related graduate programs in the United States, this fellowship offers an opportunity to work closely with professional econometricians and statisticians who develop SAS software used throughout the world. The econometrics fellow will contribute to activities such as research, numerical validation and testing, documentation writing, creation of examples of applying SAS econometric software, and assisting with software development work. Specific projects assigned will be adjusted to skills and interests of the fellow selected. This program provides an excellent opportunity to explore software development as a career choice.


    The selected SAS fellow receives a monetary award for acceptance into the program, twelve-week internship salary, and housing accommodations if the student does not reside locally to our Cary, NC headquarters.


    To be considered for this summer Fellowship opportunity, you must submit your application along with a copy of your resume by January 31, 2019.  You must also ensure that 2 faculty members from the university/college you're currently attending send a letter of recommendation to this email address:




    • PhD. candidate in economics, statistics, finance or related graduate program in the United States, with at least 2 years of graduate studies completed by the end of the spring 2019 semester
    • Demonstrated experience in statistical computing beyond the routine classroom use of statistical packages
    • Good written and verbal communication skills



    We are particularly interested in candidates with a combination of computational and research experience in one or more of the following areas:

    • Panel data methods
    • Discrete choice modeling and market research methods
    • Stochastic frontier modeling
    • Bayesian econometrics methods
    • Spatial data regression modeling techniques (such as SAR, SEM, SARMA models), spatial diagnostic tests, spatial data visualization, and construction of spatial weighting matrices
    • Sequential Monte Carlo methods and hidden Markov models for multivariate time series
    • Multivariate time series methods for data sampled at mixed frequencies
    • Dynamic factor models



    Additional Information:

    SAS is an equal opportunity employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other characteristic protected by law. To qualify, applicants must be legally authorized to work in the United States and should not require sponsorship for employment visa. For more information, see the following documents: Equal Employment Opportunity is the Law, EEO is the Law, and the Pay Transparency notice.



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