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Land IQ, LLC is seeking a Remote Sensing Scientist in its Sacramento, California office with a specialization in data driven analytics and algorithm development with digital images for agricultural and other land use applications (crop classification, yield modeling, land use impacts, land use change, etc.
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Our areas of expertise include remote sensing, geospatial analysis, GIS, soil science, water quality and demand evaluation, agricultural systems, salinity and nutrient management, ecosystem restoration, statistics, and regulatory policy.
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The successful Remote Sensing Scientist candidate will be responsible for working with our growing geospatial team comprised of remote sensing/GIS experts and a range of agronomic, environmental, and other land-based science disciplines.
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BS/MS Remote Sensing/Geography/Data Sciences field (advanced degree preferred) Proficient at remote sensing modeling (e.g., data cleaning, feature selection, analysis, designing, building, and model assessment.
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Remote sensing-based land cover mapping over agricultural areas and crop classification; Applicants must have strong analytical, remote sensing and GIS skills and an exceptionally strong understanding of machine learning algorithms.
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Develop and implement remote sensing and statistical methodologies to perform land use and land cover classification (crop classification) Work in a team environment on a wide range of projects, supporting our team of scientists, remote sensing analysts, and GIS analysts.
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Remote sensing of crop evapotranspiration; and/or. Resourceful in seeking, preparing, and/or creating raster & vector data. Develop innovative image analysis solutions using a wide array of data sources.
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Familiar with deep learning platforms (e.g., Keras, Tensorflow) and related classification and segmentation algorithms. Proficient at machine learning algorithms, familiar with algorithms like Generalized Linear Model, Random Forest, CART, and/or deep learning.
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Perform and develop advanced object-based image analysis procedures and methodologies for earth science applications. Leverage a strong understanding of multispectral imagery characteristics to solve complex agricultural and environmental land-based problems.
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Develop and perform raster-based imagery analysis procedures, spatial and statistical modeling applications. Image based time series analysis and crop phenology modeling; Understand geospatial challenges and conceptualize and articulate analysis approach ideas within a multi-disciplinary team.
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Image based crop yield modeling. Land IQ specializes in providing solutions to challenging agricultural and environmental problems throughout the western United States. Experienced in Python packages like NumPy, SciPy, Geopandas, Matplotlib, Scikit-Learn, Keras.
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Desirable skills and experience include synthetic aperture radar image science or analysis; other remote sensing imaging such as multispectral; programming and script development; data science; Python, Databricks, Jupyter Notebook; Intelligence Community analytical workflows.
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Axle is seeking a Data Scientist - Data Quality to join our vibrant team at the National Institutes of Health (NIH) supporting the National Center for Advancing Translational Sciences (NCATS) located in Rockville, MD.
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This is an environmental consulting position requiring ability to develop analysis approaches/methodology and work within a team to optimize methods. Proficient at advanced spatial analysis and geoprocessing (e.g., image segmentation, object-based image analysis.
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Enthusiastic about collaborating with team members to reach team and organizational goals. Strong organizational, communication and writing skills, positive/enthusiastic attitude, passionate about professional pursuits, personable, ability and desire to learn, and attention to detail, strong moral and ethical personal standards.
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