Patent Data Analyst - Marketing, Entrepreneurship and Innovation (part-time/temporary)

University of Massachusetts Lowell
March 19, 2023
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Patent Data Analyst - Marketing, Entrepreneurship and Innovation (part-

time/temporary)

Apply now Job no: 517898 Position type: Hourly Benefit Status: Non-Benefited – Non-Union Campus: UMass Lowell Department: Mktg Entr & Innovation Salary: Salary commensurate with experience Applications Open: Feb 16 2023 Applications Close: Open until filled

General Summary of Position:

The candidate will work as a patent data analyst for the research project “Corporate green transition and technological innovation”, under the supervision of the project PI.

Essential Job Duties:

First, the candidate will be responsible for collecting data from multiple data sources, including United States Patent and Trademark Office (USPTO) PatentsView, Global Reporting Initiative (GRI), COMPUSTATA, and SDC database. The candidate will need to create computer programs to download data from data sources above. Second, the candidate will be responsible for calculating a series of first-order and second-order indicators at the patent, firm, and patent class level, on the basis of the raw datasets, including the number of forward citations in 3-5 years, the number of forward citations in each World Intellectual Property Organization (WIPO) International Patent Classification (IPC) class and subclass in 3-5 years, the number of backward citations and backward citations in each WIPO IPC class and subclass, the emergence of breakthrough innovation, search depth, scope, and scale, exploitative innovation and exploitative innovation, green patent, patent originality, patent generality, and complexity. Third, the candidate will also help with data matching and cleaning. The candidate will need to create proper fuzzy matching programs and use them to link different datasets. The candidate should evaluate the effectiveness and efficiency of the fuzzy matching programs. Fourth, the candidate will need to help set up empirical models, including DiD, SEM-PLS, PSM, and HLM. The candidate will work with the project PI to determine the final empirical model.

Estimated total workload: 200 hours. Estimated weekly workload: 20 hours. Hourly rate: Competitive and commensurate with the candidate's experience

Minimum Qualifications (Required):

  • The candidate should have related experience and background in data science, particularly patent data collection, cleaning, and curation, and know how to create proper computer programs.
  • The candidate should also have advanced knowledge in empirical research.
  • The candidate should know data analysis techniques, including difference- in-difference (DiD), matching technique, structural equation model- partial least square (SEM-PLS), propensity score-matching (PSM) analysis, and hierarchical linear model (HLM).
  • Special Instructions to Applicants:

    Review of applications will begin immediately and continue until the position is filled. However, the position may close when an adequate number of qualified applications is received.

    This is a temporary, part-time, non-benefited, non-unit position.

    Please include a resume, research publications and sample of scholarly work/publications with your application. Names and contact information of three references will be requested at the time of application. Submission of a cover letter is optional.

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