Full-Time/Exempt (Salaried) contract position with CSS-Dynamac (40 hrs per week)
Job ID: 2014-1615 Location: Silver Spring, MD, USA; National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) Posted Date: 07/24/2014 Category: Science/Engineering Security Clearance Level: National Agency Check (Client Initiated) Apply for this job online at: https://jobs- consolidatedsafety.icims.com/jobs/1615/wildlife-statistician-spatial- modeler/job Position Description: Seeking a Wildlife Statistician/Spatial Modeler with demonstrated experience fitting advanced statistical spatial/spatiotemporal models to wildlife survey data (e.g., seabirds and marine mammal transect surveys, fisheries trawl surveys). An individual with experience in marine sciences is strongly preferred. This statistician/modeler will help to conceive and execute spatial analyses and generate predictive maps of species distributions to support marine ecosystem management, conservation and planning. The initial assignment for this position will involve building on an existing code base and executing machine-learning models for predictive spatiotemporal modeling of marine bird and mammal distributions in the Pacific Northwest. Other potential projects include predictive modeling of deep sea corals, sea turtles, marine fish, fishing fleets, and marine ecosystem processes in a variety of US jurisdictions. The successful candidate will become a member of an interdisciplinary research team supporting the NOAA National Centers for Coastal Ocean Science (NCCOS) Biogeography Branch (http://coastalscience.noaa.gov/). The NCCOS Biogeography Branch is a nationally recognized scientific program that conducts research, monitoring, mapping, statistical modeling, assessment and forecasting of marine ecosystems. The candidate will be employed by CSS- Dynamac, but will be located at the NCCOS Biogeography Branch working as a member of an integrated team of contractors and Federal employees. Essential functions: Primary responsibilities will include: 1) using large-scale wildlife surveys and oceanographic databases to describe patterns in marine mammal and bird populations through space and time; 2) applying an existing machine-learning modeling framework coded in R to generate species distribution and abundance models, 3) growing an advanced spatial analysis code base, and oceanographic and ecological geodatabases, 4) leading analysis of model outputs, and generating tables and figures linking results to project objectives; 5) providing general statistical guidance to team members; 6) traveling to laboratories and institutions as part of collaborative research projects; and 7) contributing to peer-reviewed publications and technical reports in support of projects. Qualifications and Experience: Required: - Masters degree or equivalent experience in Quantitative Ecology, Applied Ecological Statistics, or similarly highly quantitative field. An advanced degree in subjects such as Ecology or Marine Science is also acceptable with demonstrated evidence of a strong quantitative focus and statistical programming; - Expertise executing spatially-explicit models in R and/or Matlab (a code sample may be requested to demonstrate proficiency); - Demonstrated ability to independently identify, analyze and solve complex statistical model fitting challenges, work with large data sets, and think creatively about connections between wildlife, places, and people; - Excellent written and oral scientific communication skills; - Able to work effectively in a dynamic, fast-paced, team-oriented, multi- project environment; - Non-U.S. citizens must possess current documentation authorizing employment in the United States; - Processing of a National Agency Check and Inquiries (NACI) and fingerprinting will be required. Preferred: - Ph.D. or equivalent experience; - Knowledge of marine science and oceanography; - Experience analyzing wildlife survey data, especially marine mammal and seabird data; - Experience with a range of statistical modeling techniques including geostatistics and assessment of model performance and uncertainty; - Experience working with ocean remote sensing data and numerical ocean model outputs; - Experience interfacing with oceanographic, remote sensing, ecological and environmental data repositories (e.g., ERDDAP, OpenDAP, THREDDS, OBIS); - Proficiency with programmable GIS (e.g., Python scripting with ArcGIS); - Experience with parallel/cluster computing in Windows PC and Linux environments; - Record of academic publication. Please note that this position description is on the CSS-Dynamac website (http://www.css-dynamac.com/) in a condensed form. Apply for this job online at https://jobs- consolidatedsafety.icims.com/jobs/1615/wildlife-statistician-spatial- modeler/job
