Data Scientist​/Ocean Engineer

Job Description

NOAA NCCOS seeks highly qualified candidates for a Data Scientist/ Ocean Engineer position on an interdisciplinary research team of contract and federal employees supporting the NOAA National Centers for Coastal Ocean Science (NCCOS) Marine Spatial Ecology Division (MSE) ((Use the "Apply for this Job" box below).). NCCOS is a nationally recognized scientific research program that conducts spatial ecological analysis, statistical modeling, ecological forecasting, and predictive mapping to support marine ecosystem management, conservation, and spatial planning.

The candidate will be employed through a labor contract supporting the NOAA National Ocean Service in Beaufort, NC.

• We seek candidates with demonstrated expertise in signal processing and creating macros or scripts to automate processing of data from remote or underwater sensors, and artificial intelligence / machine learning for computer vision and related tasks to characterize marine environments. MSE analyzes imagery to characterize underwater habitats, from the species and benthic substrates, to the larger-scale, ecological communities and ecosystems. Imagery may be collected from remote sensing platforms such as sensors on satellites, aerial drones, uncrewed surface vessels or autonomous underwater vehicles.
  
  Traditionally, MSE spatial analysts have manually interpreted and annotated the content of these imagery data sets to determine the types of benthic biological coverage (e.g., coral or seagrass) and substrate type (e.g., mud or sand), which is a time-intensive and subjective process. Automation and machine learning present scalable solutions for the MSE processing routines, specifically to
  1) reduce human annotation effort,
  2) reduce human‑induced errors and bias,
  3) enhance reproducibility for auditing, and
  4) optimize pattern detection unapparent through manual analysis.
• The principal initial objective of this effort will be to focus on developing more efficient macros, scripting and AI‑based techniques and workflows to assist in annotation and extraction of habitat information derived from underwater imagery and point clouds signal processing.

Core Responsibilities:

• Assist in marine mapping related projects by working with principal investigators (PIs) to understand their project objectives, and help develop solutions for automation at scale.
• Work with other NCCOS data scientists to facilitate deployment of automation and AI solutions on local machines or cloud environments.
• Implement and / or develop computer vision and machine learning algorithms for analyses, including algorithms for model selection, validation, skill assessment, and ground‑truthing.
• Lead and contribute to peer‑reviewed publications, presentations, and technical memoranda.
• Provide analytic and technical guidance to team members.
• Travel to federal and state laboratories, academic institutions, and field missions as part of collaborative research projects (