[ES_JOBS_NET] Data Engineer, Truckee CA, Conservation Science Partners

[Meghan Halabisky]

Position: Data Engineer
Deadline: August 31

Conservation Science Partners is a leader in the fields of conservation
biology and landscape ecology, working at the intersection of the latest
computational technologies and the environmental sciences. We seek a Data
Engineer to provide project-specific support, as well as leadership, on a
wide array of high-profile, data-driven projects or initiatives. We work in
the exciting, complex, and fast-paced nonprofit realm where the emphasis of
projects is generally on terrestrial ecology and freshwater systems, with
applications to human systems (e.g., land and water use, protected areas,
social and environmental justice, end-user needs) using tools that include:
data science and advanced analytics; disturbance, drought, impacts, or risk
analysis; climate change vulnerability analyses; species occupancy and
habitat modeling; and wildlife and ecological connectivity analysis, among
others. The position will serve as part of a team of data scientists and
ecologists working to solve large-scale problems through implementation of
end-to-end software development workflows, machine learning/advanced
statistical modeling, and cloud based computing tools. This individual will
work closely with teams based in two offices (CA and CO) plus affiliated
locations or institutions in four other western states. The successful
candidate will contribute to an internal culture of diversity, equity,
inclusion, innovation, creativity, and experimentation, and help to advance
the function, direction, and initiatives of the organization.

Core responsibilities for this position include: ● Designing and
implementing data processing and ingestion pipelines using a portable
reproducible science workflow that includes using version control workflows
(git), containerized environments (docker), and utilizing cloud based
computational resources (e.g. Azure, Amazon Web Services, and/or Google
Cloud Platform). ● Engineering of features from a variety of data types
(e.g. imagery, video, tabular, etc.) for training, validation, and testing
datasets. ● Designing and implementing supervised/unsupervised machine
learning, deep learning (Tensorflow, Keras, and/or PyTorch), and Bayesian
statistical models (Stan, JAGS, and/or greta). ● Contributing to the
design, development, and management of multiple research initiatives or
projects simultaneously; liaising directly with diverse project partners or
clients, as needed. ● Developing or supporting manuscripts, reports,
proposals, professional presentations, and science communication tools. ●
Helping to promote a culture of diversity, creativity, innovation, and
experimentation in CSP.

For more information on the job description and how to apply. Please go to
our job page:

https://www.csp-inc.org/jobs/



-- 

Meghan Halabisky, Ph.D.
Lead Scientist
Conservation Science Partners
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