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Qualifications: Bachelor’s Degree Intermediate to Advanced skills in data analysis and data governance tools (, SQL, SAS, TOAD, Python, Hadoop, Teradata, Snowflake, Tableau, Collibra, Infosphere, Alation, etc.
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Perform analysis of benchmark to actual on coding related Key Performance indicators Monitor and track coding holds, denials. The CE is responsible to prevent coding denials through quality and quantitative analysis, tracking and monitoring post education performance.
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At Glumac, our fully integrated MEP, Energy Analysis, Sustainability, Commissioning, Technology, and Lighting teams are working together to meet that goal and deliver a sustainable future. Our services include MEP design, Net Zero Energy, lighting design, commissioning, vertical transportation, low voltage, information technologies, security, fire engineering, sustainability consulting, and acoustics.
$100,000 - $125,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The successful candidate must be familiar with probabilistic risk assessment (PRA) including fault tree development and quantification, reliability engineering methods (including time-dependent reliability predictions, allocations, and growth), failure modes and effects analysis (FMEA), hazard and operability analysis (HAZOP), maintainability predictions (mean time to repair), human factors / human reliability analysis (HRA.
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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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Proficient at remote sensing modeling (e.g., data cleaning, feature selection, analysis, designing, building, and model assessment). Perform and develop advanced object-based image analysis procedures and methodologies for earth science applications.
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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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Develop innovative image analysis solutions using a wide array of data sources. This is an environmental consulting position requiring ability to develop analysis approaches/methodology and work within a team to optimize methods.
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Proficient at advanced spatial analysis and geoprocessing (e.g., image segmentation, object-based image analysis). 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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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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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. BS/MS Remote Sensing/Geography/Data Sciences field (advanced degree preferred) Familiar with deep learning platforms (e.g., Keras, Tensorflow) and related classification and segmentation algorithms.
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Education: BS/MS Remote Sensing/Geography/Data Sciences field (advanced degree preferred) Proficient at machine learning algorithms, familiar with algorithms like Generalized Linear Model, Random Forest, CART, and/or deep learning.
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Leverage a strong understanding of multispectral imagery characteristics to solve complex agricultural and environmental land-based problems. Resourceful in seeking, preparing, and/or creating raster & vector data.
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Remote analysis job
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