DescriptionJOB DESCRIPTION: The Data Analyst School Year Internship is a part-time, in-person position designed for students who are currently enrolled in a college or university. To support participation during the academic year, candidates should reside in or attend school within the Texas Panhandle region. Locations include, but are not limited to, Amarillo, Canyon, Claude, Childress, and surrounding communities.
Position Summary: The Data Analyst Intern will help to drive informed decision-making by extracting insights from diverse data sources. The intern may assist the project team or departments by developing and maintaining reporting and analytical tools (Excel, Smartsheet, Power BI), cleaning data and ensuring data quality, ensuring data privacy and security, data visualization and reporting, and other duties as assigned. The Data Analyst Intern will also help prepare construction data for data science initiatives. The work commitment during the school year is roughly 20 hours per week. You will work with your team to come up with a work schedule that will allow you to achieve 20 hours per week of work time during your school year.
Salary Range: $25.13 - $31.50 per hour (plus assignment adjustment, if applicable)
Principle Responsibilities:
- Extract, transform, and load data from diverse data sources for data analysis and reporting uses.
- Check for data quality and clean data, if necessary.
- Help to maintain reports and dashboards for Department Managers and Project Managers.
- Create reports and dashboards in Power BI.
- Assist the data analyst on a construction project with duties as assigned.
- Help to mine historical construction data and improve data quality where needed.
- Assist in data strategy efforts, including updating data flowcharts and creating data swim lanes.
- Assist in data science efforts such as identifying current construction activities where machine learning or Python automation might be useful, sourcing data for data science activities, preparing data for data science activities, training, and testing machine learning algorithms, and building data science workflows.
- Host a meeting with the objective of teaching the Data team something new.
- Write and publish meeting minutes. Follow up on meeting action items.
- Complete data course(s) in DataCamp, Enterprise DNA, and/or LinkedIn Learning.