This position provides expertise in geospatial data science and location intelligence and develops analytical models/scripts, web applications, visualizations/maps, and reports in support of a wide range of research, academic, and administrative projects. Other duties include: develop and apply HPC and GIS methods to identify, collect, process, and analyze large volumes of data to build and enhance research products, processes, and systems; conduct data mining and retrieval, and apply statistical and mathematical analyses to identify trends, solve analytical problems, optimize performance, and gather intelligence; visualize information using a range of tools (e.g., GIS, R, MATLAB), develop scripts and algorithms, create explanatory and predictive models, and conduct comparative analyses to address complex problems.

Minimum Qualifications
Master’s of science degree in data science, environmental science, geography/GIS, computer science, engineering, statistics, machine learning, or a related discipline. Considerable experience in developing and carrying out analytical and visualization strategies with geospatial data in a high- performance computing environment. Considerable experience using spatial and statistical analysis techniques with disparate data sets to solve problems. Considerable experience of applied statistics, probability, data modeling techniques, and predictive modeling techniques. Prior working experience manipulating and analyzing remote sensing data (UAV and satellite). Comprehensive knowledge of GIS data, concepts, methods, and software (Esri ArcGIS Suite and opensource). Considerable knowledge of GIS- and HPC-related programming languages and scripting languages (e.g.Python, R, JavaScript). Working knowledge of the following: predictive analytics, machine learning, automated data classification, knowledge discovery in databases, optimization, experimentation, and time series analysis. Proficient skill in the use of a high-level analysis tool or statistical language (e.g. R, SAS, SPSS, MATLAB). Demonstrated ability to conceptualize and complete complex projects with thorough documentation and demonstration of applied logic. Demonstrated ability to communicate effectively with people of various technical backgrounds, think analytically, write and edit technical material, and relate data science concepts to technical and non-technical stakeholders. Demonstrated ability to understand and translate domain researchers’ scientific goals into analytical strategies and process requirements. Demonstrated ability to work independently and manage time efficiently.

Preferred Qualifications

Doctorate degree in data science, environmental science, geography/GIS, computer science, engineering, statistics, machine learning, or a related discipline or an equivalent combination of education and experience. Comprehensive knowledge of the application of scripting and programming languages to geospatial analysis, models, and solutions. Prior working experience with tools in the scientific/geospatial python stack. Prior working experience developing scripts, models, and using machine learning to solve and automate classification, regression, cluster analysis, anomaly detection, association discovery, and spatial modeling tasks. Prior working experience working with large-volume datasets, those likely requiring novel data structures and/or parallelized workflows for analytical processing. Prior working experience developing data dashboards and web applications. Prior working experience with physical process models and data assimilation. Prior working experience with deep learning and neural networks. Prior working experience with data visualization tools like Periscope Data, Data Studio, Tableau or similar related software. Comprehensive knowledge of the application of scripting and programming languages to geospatial analysis, models, and solutions. Strong general computational and programming skills, including experience in a programming language used in scientific computing, and competency with UNIX/LINUX shell environment. 

ODU Statement

Old Dominion University, located in the City of Norfolk in the metropolitan Hampton Roads region of coastal Virginia, is a state-assisted, Carnegie doctoral/research-extensive institution that serves its students and enriches the Commonwealth of Virginia, the nation, and the world through rigorous academic programs, strategic partnerships, and active civic engagement. Its 24,000 students, including over 6,000 graduate students, form a diverse and multicultural community in six academic colleges. Through a collaborative and innovative approach to education and research, the University focuses on student learning and addresses critical needs in the professions. ODU’s programs are offered on the main campus, at higher education centers in the region, and at numerous distance learning sites.

It is the policy of Old Dominion University to provide equal employment, educational and social opportunities for all persons, without regard to race (or traits historically associated with race including hair texture, hair type, and protective hairstyles such as braids, locks, and twists), color, religion, sex or gender (including pregnancy, childbirth, or related medical conditions), national origin, gender identity or expression, age, veteran status, disability, political affiliation, sexual orientation or genetic information. Minorities, women, veterans and individuals with disabilities are encouraged to apply.