Software Developer & Geospatial Data Analyst - IARC

University of Cincinnati

Cincinnati, OH

ID: 7079430
Posted: June 4, 2021
Application Deadline: Open Until Filled

Job Description

Position Summary:
The UAF International Arctic Research Center and the Scenarios Network for Alaska and Arctic Planning are seeking a Software Developer & Geospatial Data Analyst to join our growing team. We are scientists, designers, communications specialists, geospatial data scientists, and programmers who engage with a broad range of audiences including academics, engineers, managers, and the public. Our team applies University research to improve our understanding of Alaska's changing climate. In this position, you will work as a programmer who collaborates with multiple UAF research units and projects. You will produce and manage large-scale geospatial data to create modern, data-driven web tools and mobile applications to facilitate discovery, access, visualization, and application of research data. Your work will help provide data-focused direction for crafting realistic adaptation strategies for Alaskans.
Data Analysis & Support: Develop, modify, compile, and execute scientific model code for research projects in high-performance computing environments. Provide input and guidance to management staff to help determine appropriate data formats for applications and visualizations. Perform data processing to transform data for application in visualizations, tools, and scientific models. Collaborate with the University of Alaska research community to curate, manage, and prepare high-impact University-developed datasets in order to make them more discoverable and applicable to various applications and decision support tools.Project management, support and communication: With supervisor guidance and assistance, serve as project lead by coordinating projects with a broad scope to ensure the reliable completion of deliverable requirements in a predictable and timely manner. Utilize resources, track project progress, and communicate status appropriately. Provide technical expertise and assistance to management staff to assist with decision making or goal-setting for both internal work and as consultant to stakeholders. Coordinate and communicate with development, data, communications, and design teams to deliver applications and data. Assist end-users with software, data, and end-user applications - available periodically for operational systems on-call support for 24 hours a day, 7 days a week.Programming: With supervisor and other guidance from the team, evaluate and perform programming tasks in a variety of software languages (full-stack development). Develop full-featured web, mobile, and cloud-based infrastructure applications involving complex geospatial and database components under general supervisor guidance and collaboration with peers. Develop and perform automated and manual software tests to maintain quality control and accuracy under general supervisor guidance and collaboration with peers. Use data visualization frameworks and software libraries to produce interactive visualizations of scientific data for researchers, the public, and internal needs. Use geospatial software, frameworks and software libraries to prepare, process, and deploy geospatial web and mobile applications. With supervisor guidance, help integrate new technology into existing systems and approaches and provide training to other staff on usage. Assist end-users with software, data, and end-user applications - available periodically for operational systems on-call support for 24 hours a day, 7 days a week. Perform work under general direction.
This position will be physically located at the UAF campus in Fairbanks, Alaska. While there may be a current opportunity for remote work, the successful finalist will be expected to report to duty at the UAF office no later than 60 days from written notice provided by the university.Applicants must be legally eligible for unrestricted employment to work in the U.S. No work visas will be sponsored for this position.


Demonstrated software development skills and fluency with Javascript and Python.

Advanced knowledge of and ability to implement web applications, including single page applications, client/server architectures, and common frameworks in Javascript/Python (e.g., Vue, React, Express/Koa, Django, Flask).

Advanced skills in web-based mapping and data processing/geospatial libraries in Javascript and Python (e.g., Leaflet, Proj4JS, Pandas/Dask, Xarray, Rasterio, GDAL).

Demonstrated prior technical knowledge of critical systems and coordinating multiple project requirements in a production environment.

Ability to use automated testing frameworks (Mocha/Javascript, pytest/Python).

Knowledge of container-based workflows and management (Docker, Kubernetes) and/or cloud-based infrastructure management (AWS, etc).

Demonstrated technical analytical problem solving and troubleshooting skills, such as for identifying and analyzing bugs.

Knowledge of software development best practices, including design, coding standards, and peer review; demonstrated flexibility with using multiple approaches with different stakeholders.

Ability to implement relational database design (SQL).

Ability to use scientific and geospatial data formats (Shapefiles, GeoTIFF, NetCDF).

Knowledge of software project management and development lifecycle (Agile, Scrum, Kanban).

Ability to understand technical and non-technical project needs, communicate those needs between different stakeholder audiences.

Excellent technical communications skills: written, verbal, email, and team collaboration tools (e.g. Trello, Slack).

Able to work effectively independently and with teams of local and remote peers and stakeholders.

Knowledge of mobile app development methodology, APIs/SDKs, languages and frameworks (e.g., Android, iOS, Java, Swift, Objective-C, React-Native, Ionic).

Knowledge of and ability to use and code in C/C++, Fortran, or other low-level languages.

Knowledge of GIS and cartographic concepts, projection systems and gridding; familiarity with command-line, batch data processing techniques (e.g. QGIS, GDAL).

Ability to effectively manage and work with large amounts of data (100TB+ data sets), file organization skills.

Ability to interact and communicate with researchers professionally and clearly.

Knowledge of and ability to use statistical analysis and interpretations.


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