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Skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
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Your expertise in ETL, DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupiter Notebooks will be essential in ensuring efficient data processing and analysis. Job Responsibilities:- Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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The Environmental Scientist – Data Specialist will focus on the support of environmental systematic review projects and require an understanding of 1) environmental science and 2) data analysis/management and data visualization.
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In the role, you will collaborate with engineers and data professionals to foster the use of data science, advanced analytics, machine learning, and other techniques to amplify solutions in EC’s issue areas.
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I am writing to express my interest in the Data Science & Analysis (Digital) position at Guidehouse. Bullet Points: - Seeking Data Science & Analysis (Digital) position at Guidehouse.
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Establishing the cloud and on-premise connectivity in different systems like ADLS, ADF, Synapse, Databricks Hands on experience in Azure cloud services like Azure Data Factory or Azure Synapse, MSSQL Db, Azure SQL DB, Azure Data Lake Storage Gen2, Blob Storage, Python etc.
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Proficiency in data integration through use of analytical tools such as GIS, Matlab, Python, R, etc., preferred. Experience with FEMA Coastal flood studies and knowledge of FEMA's Guidelines and Specifications is a plus.
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You will leverage knowledge of Python or R, customize tools for select acquisition of bulk PAI data, and use internet technologies and observables, including process automation. Master's degree in International Affairs, Political Science, Foreign Area Studies, National Security Studies, Linguistics, Business, Library Science, or a related field preferred.
$150ExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as Rand Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
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Knowledge of Python data science tools, such as SciKit, Numpy, TensorFlow, Jupyter. Experience solving Big Data batch and real-time data processing problems, with large-scale analytics and data processing engines such as Apache Spark and Databricks.
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Bachelor's degree (master's degree desired) in related field required (preferably in Geography, Social or Behavioral Science, Computer Science, Information Systems, Math or Statistics, Earth or Geo Science, Life, Physical or Environmental Science, Engineering, Business, Data Science, Data Visualization.
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Location:Tysons, VA (Hybrid) with some remote work·Work Authorization:EAD, Green Card or ·Work Type:Full Time Responsibilities include, but are not limited to: Gathering and cleaning HR data from various sources, such as HRIS, ATS, surveys, and external benchmarksPerforming descriptive, inferential, and predictive analysis using statistical methods and tools, such as Excel, SQL, R, Python, Power BI, Tableau, etc.
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Minimum QualificationsBachelor's degree in Economics, Finance, Statistics, Mathematics, Computer Science, Data Science or other related quantitative field, but more competitive candidates would have a Master’s degree in the relevant field.
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You will be responsible for providing data integration and analysis services working principally with Microsoft SQL Server, though may work across a number of technologies and in several other disciplines including data modeling and data science, working with data lake-based solutions.
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Programming:Languages: Familiarity or proficiency in languages commonly used in data science, like Python, R, or Scala. Software Engineering & DevOps:Version Control: Familiarity with tools like Git. Continuous Integration/Continuous Deployment: Knowledge of pipelines and tools like Jenkins, Travis CI. Containerization: Familiarity with Docker, Kubernetes, etc., for scalable deployment of data science applications.
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data science plus python jobs Company: Endeavor in Mclean, VA
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