Senior Data Analyst
5 days ago
- Perform Traffic Data Analytics tasks like data acquisition and cleaning; processing; validation; fusion & conflation; analytics, reporting & visualization; prototype pilot client projects; and ad-hoc analysis.
- The selected Program Analyst Traffic (Part-Time) will be engaged in various aspects of Traffic Data Analytics tasks including but not limited to the following:
- Data acquisition, cleaning, and preparation tasks require working with many transportation and non-transportation data sets e.g. speed, volume, AADT(Average Annual Daily Traffic), road geometry and characteristics, socio-demographics data, posted speed limits, weather, work zone information, crash and incident data, pedestrian and bicycle data, and others, and obtaining those through different means such as graphical user interfaces, APIs, direct access to back-end databases either internally from client or third party vendor and archives.
- Data cleaning and preparation steps will be needed, especially for free-form text fields, and they may be different based on the data set and source.
- Data fusion tasks require merging or aligning (fusing) data sets on the spatial(location) or temporal (point in time or similar period of year and time of day)dimensions, in a redundant (same attributes) or complementary (different attributes) fashion.
- Data analysis and visualization tasks will require the incumbent to apply tried-and-true but also new and innovative methods to identify historical travel trends, conduct Before-and-After studies, perform congestion and reliability analyses for specified areas and periods of interest, and identify locations and periods experiencing unusual traffic behavior.
- nalysis results will be presented in a format and at a level of detail appropriate for the audience, through interactive and static charts, graphs, and maps.
- GIS and map conflation will require leveraging existing map conflation tools and algorithms, but in some cases, the development of new algorithms and methods may be necessary.
- Either way, manual checking and validation of conflation will be needed since conflation algorithms are not perfect and do not cover all real-life situations.
- Some research to perform the above tasks will be needed.
- The research will include but not be limited to a literature review of transportation data analytics algorithms, investigating the feasibility and usability of incorporating new data sources into analytics algorithms to improve the accuracy and relevance of results, and traffic forecasting methods.
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