Initiative on Operational Data Science
The Texas A&M Institute of Data Science (TAMIDS) seeks a postdoctoral Data Scientist to join its initiative on Operational Data Science. Texas A&M University is a large and complex organization, with over 69,000 students enrolled in programs over 19 Colleges and Schools in which research and instruction is led by roughly 4,000 faculty. The main College Station campus occupies 5,200 acres. Many functions of University infrastructure—including transportation, mobility, facilities and utilities—routinely collect data during their operation. The resulting data are used to manage these functions across a range of timescales—ranging from planning, through daily operations, to troubleshooting and event response—and over the large and varied campus.
The principal goals of this initiative are to: (i) identify new data-driven research problems arising from operational contexts; (ii) use Data Science to derive new insights and enable new analyses of the data and embody these in software tools that can benefit operations; (iii) help the broader community of faculty, researchers and students at Texas A&M engage with operational data challenges. Achieving these goals has the potential to transform Texas A&M into a living laboratory for applied Data Science.
Major Job Duties
The Data Scientist will work with the TAMIDS initiative on Operational Data Science and will be responsible for collaborating on projects between TAMIDS and its research partners, including the TAMU GeoInnovation Service Center, utilizing varied data provided by these and other partnering Texas A&M operational organizations.
Duties Include: Collect, assure, curate, store, and perform analytics on operational data, including integrative analysis of data from multiple sources; Leverage statistical programming languages and packages for knowledge discovery and data analysis, with an emphasis on open source software (e.g., R, Python, XGBoost, Spark, etc.); Develop software and visualization tools (e.g. web-based) that embody analysis results for use by operational partners and general users; Engage with TAMIDS partner organizations in formulating novel analyses and use cases for operational data and pursue related opportunities for new research partnerships with Texas A&M and external organizations; Serve as a point of contact and local expert concerning these data for Texas A&M faculty, researchers and students, and serve on the mentoring team for students engaged in projects concerning these data; Design and deliver occasional training workshops on data and tools, and collaborate on preparing technical presentations and conference papers on the work.
Education and Experience
Required Education and Experience: PhD is an area related to Data Science. Years of experience commensurate with level of appointment.
Preferred Education and Experience: Strong academic background in statistics, computer science, electrical engineering, mathematics, or similar discipline. Significant experience in foundations and/or applications of Data Science in an academic, industrial, government on non-profit setting, commensurate with level of appointment.
Required Special Knowledge, Abilities or Skills: Significant experience in research and applications of Data Science in one or more operational domains and associated disciplines including but not limited to: transportation, mobility, facilities management, environmental sensing, image and video interpretation, geospatial data processing. Ability to multi-task and work cooperatively with others.
Interested candidates should apply by email to email@example.com attaching a research statement, resume, and contact information for three referees.
Equal Employment Opportunity Statement
Texas A&M University is committed to enriching the learning and working environment for all visitors, students, faculty, and staff by promoting a culture that embraces inclusion, diversity, equity, and accountability. Diverse perspectives, talents, and identities are vital to accomplishing our mission and living our core values. Equal Opportunity/Affirmative Action/Veterans/Disability Employer committed to diversity.