Duke Parking & Transportation Services (PTS) provides oversight for more than 27,000 parking spaces within eight multi-level garages and greater than 75 surface lots as well as a transportation system that moves 3.5 million riders annually. The Data Analyst, embedded within the PTS offices, will play a pivotal role in improving the department’s operational efficiency through the use of existing and new technology and by developing the analytical framework, data architecture, applications and tools for data-driven decision making. This position will be responsible for creating and interpreting analytic tools and dashboards and must stay abreast of rapidly advancing innovations within parking and transportation.
The successful candidate will be responsible for the following:
Coordinate and participate in a variety of duties involved in collecting, interpreting, documenting, and summarizing descriptive, analytical, and evaluative data in support of research and/or information gathering activities.
Gather information and data from various sources on problems (areas of improvement) that might help better understand the situation. Analyze, study, and interpret the information to find patterns and trends, validate data quality, and disregard irrelevant data.
Filter and “clean” data, and review reports, logs, and performance indicators to locate and correct code problems.
Collect data using a variety of methods, such as data mining and hardcopy or electronic documentation to improve or expand databases. Ensure database is free of any duplicated, out of date, or irrelevant information.
Coordinate and monitor the design, development, modification and implementation of data collection and reporting applications; provide and design tools to assist in the management of the database and client/server environment; provide backup and recovery services.
Work with appropriate resources to establish procedures and protocols for the procurement of data via a variety of methods; observation, interviewing, electronic records and other sources. Standardize methods to collect, analyze and manage data to improve data quality and the efficiency of data systems.
Design reports including tools, such as statistics, graphs, images, and lists that can help the interested parties easily digest and interpret the data. Communicate the results, as well as recommendations of the data analysis as a comprehensive report to decision makers and others affected by the results, noting trends, anomalies, and significant statistical variances and deviations of complex data sets.