• Research Software Engineer

    Requisition # 2019-10347
    Date Posted 4 months ago(5/13/2019 2:02 PM)
    Department
    Population Research
    Category
    Research and Laboratory
    Full-Time / Part-Time
    Full-Time
  • Overview

    The Center for Research on Child Wellbeing (CRCW) at Princeton University is seeking a Research Software Engineer to collaborate on research and provide computational expertise in data engineering, applied machine learning, and optimization in order to create efficient and scalable research code. This position will have a significant role in designing and conducting additional research building on the Fragile Families Challenge. This position will work with the project Principal Investigator (Matthew Salganik) and will contribute to the research community at Princeton, including the community focused on the Fragile Families and Child Wellbeing Study (FFCWS).

     

    The ideal candidate will have a strong background in statistics, machine learning, and data engineering. They will be able to translate academic research into production quality, stable and documented code.

     

    This is a one-year term position with the possibility of renewal based on performance and continued funding. 

    Responsibilities

    • Participating in ongoing research related to the Fragile Families Challenge.
    • Developing new data pre-processing techniques for the FFCWS data.
    • Assessing the performance of different predictive modeling techniques on subsets of the FFCWS data.
    • Deploying these techniques to other longitudinal datasets.
    • Developing open source software---or contribute to existing open source software---so that other researchers can more easily perform the same research.

    Qualifications

    Essential:

    • A bachelor's degree in computer science, engineering, sciences, or related computational field required or a Masters/Ph.D. in computer science, applied science, or other related field with a strong computational focus preferred.
    • Strong programming skills, particularly in the languages used in social data science applications:
      • Python,
      • R, and/or
      • C/C++.
    • Strong background in statistics and machine learning.
    • Experience with modern software development practices:
      • version control,
      • unit testing,
      • continuous integration,
      • packaging/distribution.
    • Ability to learn new systems beyond area of core knowledge.

     

    Preferred:

    • Parallel programming experience on workstations and computational clusters.
    • Frontend programming experience (web or desktop graphical interfaces).
    • Academic research experience.
    • Experience with fraud detection or other techniques focused on outliers. 
    • Experience with FFCWS data, or with other large, longitudinal social science datasets (PSID, Add Health, NLSY, etc.).

     

     

    Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. EEO IS THE LAW

    Salary Grade

    AIT, 020

    Standard Weekly Hours

    36.25

    Eligible for Overtime

    No

    Benefits Eligible

    Yes

    Essential Services Personnel (see policy for detail)

    No

    Estimated Appointment End Date

    6/3/2020

    Physical Capacity Exam Required

    No

    Valid Driver’s License Required

    No

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