Geospatial Data Scientist
- Employer
- Old Dominion University
- Location
- Virginia, United States
- Salary
- Salary Commensurate with experience
- Date posted
- Jul 7, 2021
View more
- Position Type
- Administrative, Business & Administrative Affairs, Computer Services & Information Technology
- Employment Level
- Non-Tenured Track
- Employment Type
- Full Time
Information Technology Services (ITS) at Old Dominion University
is accepting applications for the Geospatial Data Scientist
(full-time, 12 month) position. 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.
Required Education: Master’s of science degree in
data science, environmental science, geography/GIS, computer
science, engineering, statistics, machine learning, or a related
discipline.
Required Qualifications: 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 Education: 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.
Preferred Qualifications: 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.
Review Date: The initial application review date
for this position is July 27, 2021 and will remain open until
filled.
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.
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