Student Hourly Assistant - Data Annotation & Visualization Support job opportunity at Prairie View A&M University.



DatePosted 26 Days Ago bot
Prairie View A&M University Student Hourly Assistant - Data Annotation & Visualization Support
Experience: General
Pattern: part-time
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degreeGeneral
loacation Prairie View, TX, United States Of America
loacation Prairie View, ..........United States Of America

Job Title Student Hourly Assistant - Data Annotation & Visualization Support Agency Prairie View A&M University Department School Of Architecture Proposed Minimum Salary $12.50 hourly Job Location Prairie View, Texas Job Type Student Worker Job Description We are seeking a highly motivated and detail-oriented undergraduate student to support a data-driven architecture and engineering research project. The successful candidate will assist with data annotation, visualization, and basic Python scripting to support undergraduate learning and research workflows. Job Responsibilities: Assist with annotating datasets related to the built environment and smart building applications. Develop simple Python scripts to help undergraduate students visualize data sets (e.g., using Matplotlib, Seaborn, or Plotly). Create clear, well-documented code templates for generating graphs, charts, and basic dashboards. Support faculty and students in formatting and preparing data for use in workshops and class modules. Collaborate with the research team to track and refine labeling and annotation standards. Required Education and Experience: Presently enrolled at Prairie View A&M University for at least nine (9) graduate or six (6) undergraduate semester credit hours during the term in which the work is to be done. Must be in good academic standing (SAP) as demonstrated through your college; minimum 2.0 GPA Sophomore level or above No prior experience necessary For work eligibility during a summer term, a student must be enrolled for at least three (3) graduate or undergraduate semester credit hours during the term in which the work is to be done or preregistered at least six (6) undergraduate semester hours or nine (9) graduate semester hours for the upcoming fall term. Preferred Education & Experience Enrolled in Computer Science, Engineering,  or related fields Intermediate proficiency in Python, especially for data handling and visualization. Familiarity with Jupyter Notebooks, Pandas, and data wrangling tools. Attention to detail and consistency in data processing tasks. Excellent communication and collaboration skills. Preferred Knowledge, Skills, Abilities Familiarity with machine learning or large language models (LLMs). Prior experience in training or evaluating AI models. Exposure to AI in AEC, geospatial data, or environmental analytics. Required Attachments: Please attach all required documents listed below in the attachment box labeled as either “Resume/CV or Resume/Cover Letter” on the application. Multiple attachments may be included in the “Resume/CV” or Resume/Cover Letter” attachment box. Cover Letter (Optional) Resume Detailed Class Schedule Application Submission Guidelines: The required documents listed in the above-Required Attachments section must be attached to the application prior to the job closing date indicated to ensure full consideration for the application submitted. Please contact the Office of Human Resource on or before the closing date indicated above at 936-261-1793 or seo@pvamu.edu should you need assistance with the online application process. All applicants are required to apply via our Career Site on or before the closing date indicated on the job posting. Applicant inquiries received via email and websites such as Indeed, HigherEdJobs, etc. will not be considered unless the individual has applied to the available position via the PVAMU career site. All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution’s verification of credentials and/or other information required by the institution’s procedures, including the completion of the criminal history check. Equal Opportunity/Veterans/Disability Employer.

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