Software Engineer

University of Washington•Seattle, WA

10h•$87,624 - $98,400•Onsite

About The Position

Columbia Basin Research has an outstanding opportunity for a Software Engineer to join their team . The Software Engineer will work with a small team of statisticians at Columbia Basin Research (CBR ; www.cbr.washington.edu ). CBR is a research center within the School of Aquatic and Fishery Sciences, College of the Environment, University of Washington. CBR conducts basic and applied research on the impacts of regulated river operations on the freshwater and marine survival of salmon in a changing environment. As part of its mission, CBR develops desktop and web-based applications (https://www.cbr.washington.edu/analysis) to perform statistical analyses relevant to fish, dam, water, and natural resource management. The Software Engineer will play a lead role in the development and maintenance of desktop applications to implement statistical analysis for effective monitoring and research related to salmon survival and migration in tributaries, past dams, and in the marine environment. These analysis tools are used by researchers and managers throughout the Columbia River Basin and California’s Central Delta to design field studies of salmon and steelhead migration and analyze the resulting tagging data. The Software Engineer will also be instrumental in redeveloping, implementing, and maintaining a web-based application to forecast salmon run-timing from a long time series of past migration data combined with data from the current migration season (“in-season forecasts”). These forecasts are used by managers of hydroelectric projects to schedule their dam operations throughout the year to protect endangered salmon and steelhead, while also providing visualizations of salmon populations’ response to hatchery practices and climate change. This position offers great opportunities for professional and personal growth in a stimulating research environment on applied ecology and endangered salmon and steelhead.

Requirements

Bachelor’s degree in Computer Science, Mathematics, Statistics, Data Science, or related field and three years of relevant experience in software development. Equivalent education and/or experience may substitute for minimum qualifications except when there are legal requirements.
Programming experience in C# or C/C++
Working knowledge of relational databases using SQL
Working knowledge of numerical optimization
Working familiarity with version control using Git
Working familiarity with Python and R
Experience with web design and Linux
Demonstrated ability to work in a collaborative setting with an interdisciplinary research team
Strong written and oral communication skills
Demonstrated problem-solving skills
Demonstrated ability to exercise logical judgment and work independently
Demonstrated ability to prioritize work to complete deliverables in a timely manner
Demonstrated ability to learn new software frameworks, understand complex quantitative methods quickly, and innovate independently and collaboratively
Demonstrated ability to establish and maintain positive, ethical, and professional interpersonal relationships

Nice To Haves

Master’s degree in Computer Science, Mathematics, Statistics, Data Science, or related field and at least three years’ experience in software development or equivalent combination of education/experience
Academic training in Mathematical Statistics or Data Analysis
Two years’ experience in Qt, XAML, Java, and Perl
Two years’ experience programming machine learning, neural networks, or other AI for time series forecasting
At least three years of experience programming with a collaborative team
Outstanding interpersonal skills, including team ethics and relationship-building, and critical thinking skills
Interest in biological/ecological subjects and the desire to develop user-friendly software to investigate environmental issues
Knowledge of Pacific Salmon and Steelhead ecology

Responsibilities

Develop and Maintain Statistical Tools and Programs: 50%
Redevelop, Implement, and Maintain Web-based Application for In-season Forecasts: 20%
Data Processing and Analysis: 10%
Customer Service: 10%
Learning New Technologies: 10%