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Using tools such as Snowflake and/or Databricks, they will also work with cutting-edge DevOps technologies, develop advanced analytics products, and apply data and statistical programming tools to enterprise data to advance and enable key mission outcomes within cloud environments (GCP, AWS, Azure.
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Proving specialization background in data science, including experience with statistical analysis, data mining, predictive modeling, and machine learning; Data Processing/Analytics/Science, Computer and Information Science, Statistics.
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Participates in specific program activities such as landfill testing, asbestos removal, and soil aeration, including evaluation and review of plans and permits, field-testing and observation, data analysis, and report preparation.
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Established in 1946, with headquarters in Arlington, Virginia, AIR is a nonpartisan, not-for-profit institution that conducts behavioral and social science research and delivers technical assistance to solve some of the most urgent challenges in the U.S. and around the world.
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Proficiency with the modern Python data science stack including numpy, pandas, matplotlib, sklearn, pytorch, beautifulsoup, selenium. Stay informed about the latest advancements in data science, AI, and related technologies, and incorporate new ideas and techniques while helping coach junior team members.
$95,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Bachelor's degree or masters’ degree in Engineering, Architecture, Building Science, Construction Management, or a related field from an accredited college or university; Professional Engineer, Project Management, Certified Construction Manager, Certified Public Accountant, American Institute of Architects, or other professional certification is preferred.
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1+ years' experience in performing in a data science role within analytics teams. Master's degree in a highly quantitative field (Computer Science, Statistics, Mathematics, Bioinformatics, Computational Biology, Microbiology, Software Engineering, Biological/Chemical Engineering.
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Note: Related fields above may include archaeology, anthropology, architectural history, biology, botany, business administration, climatology, economics, engineering, geology, historic preservation, hydrology, political science, range management, recreation administration (outdoor resource management), watershed management, and wildlife management.
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The Mission of Sanofis MSL Team and the Medical Science Liaison is to be the trusted scientific partners in the field for external experts and decision-makers engaging in mutual scientific exchanges to accelerate data dissemination.
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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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Has an opening for an experienced Geologist or Hydrogeologist in our Sacramento or Oakland office to assist with a variety of projects including data management, site investigations and remediation.
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Master's degree in a relevant field such as management information systems, data analytics, computer science, social science, education, statistics, data science, etc.
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Work with NAS, The Nature Conservancy, and Point Blue Conservation Science staff to assess the value of alternative wetland and farm management practices and achieve research goals. The Associate, Working Lands will support habitat incentive projects tricolored blackbird conservation efforts, participate in natural resource management planning, conduct science and monitoring following established protocols, and support program staff to coordinate advocacy and projects to advance National Audubon Society's (NAS) conservation priorities in the Central Valley.
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Medical Affairs colleagues form GBUs, e.g., Medical Manager, Medical Science Liaison (MSL): Field insights, site specific collaboration as indicated by CSU, KOL management. Planning Study start-up, anticipate implementation of protocol amendments, resulting in shifts in study timelines, recruitment and retention challenges, data management and vendor related issues.
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Experience working with big data (engineering / processing) and data migration. Database Query Engine, Data Infrastructure, Data Pipelines, Data Platform, Database Security, Data Governance, Data Sharing, FoundationDB, Manageability, Metadata, Service Runtime, Snowhouse Foundation, Storage and ML Engineering.
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data science jobs in Sacramento, CA
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