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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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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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If this describes you, read on – we want to hear from you THE GAME PLAN Everyone on our team has a part to play Building multi-layer serving architectures for ML models Business intelligence tools (e.g., Tableau, Knime, Looker) Data security and privacy (e.g. GDPR, CPP) Data governance and data testing frameworks.
Full-timeExpandApply NowActive JobUpdated 24 days ago - UpvoteDownvoteShare Job
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Do you have the skills necessary to manage, understand, and analyze inhouse and customer data including text mining, developing predictive systems, risk scoring, creating efficient algorithms, data quality improvement and other related activities.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions with clients.
$81,000 - $128,000 a yearFull-timeExpandApply NowActive JobUpdated 23 days ago - UpvoteDownvoteShare Job
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There are various disciplines involved in Enterprise Data & Analytics, including: data source identification and analysis, data engineering, data visualization & data science/machine learning.
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Use analytic methods and advanced knowledge in machine learning, statistics, text mining, natural language processing, computational semantics, computer vision, and data science to develop creative solutions to complex real-world problems.
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The GeoTech Center focuses on the global, national, and economic impacts of artificial intelligence, data and machine learning, personalized medicine, additive manufacturing, nanotechnology, green energy, telecommunications networks, synthetic biology, and other new technologies on the horizon.
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And Transformation (automation, machine learning, artificial intelligence, reporting). Experience using applied statistics or machine learning in a professional or other intensive problem-solving environment with large, complex datasets.
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The role will apply statistical programming, modeling, visualization techniques, data mining, and forecasting skills to analyze challenging public sector problems. Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc.
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Apply knowledge of statistics and mathematical theory to develop and integrate new and emerging technologies, such as machine learning and deep learning concepts and techniques. Managing teams applying knowledge of essential cybersecurity policies to data management to develop data standards, policies, and procedures to facilitate and implement data mining and data warehousing programs to collect, clean, convert and standardize complex data for analysis.
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We integrate off the shelf and new development efforts to sustain and enhance existing architecture and by leveraging cloud-based computing, artificial intelligence (Al), machine learning (Client) and cross-domain transfer systems to provide cutting edge requirements management, task coordination, data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members.
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4-6 years experience in data engineering and machine learning. Deploy production-level machine learning pipelines to impact the business of our clients. Successfully lead small machine-learning projects and workstreams with measurable performance enhancements under the management of an engagement lead.
$130,000 - $165,000 a yearFull-timeExpandApply NowActive JobUpdated 23 days ago - UpvoteDownvoteShare Job
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Experienced with general programing, statistical languages, and deep learning packages used to manipulate data and build statistical and machine learning models at a large-scale, such as Python, Spark, PyTorch, Tensorflow, Keras, SQL, and SQL-like query languages for NoSQL databases.
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They also use and advise on such tools as machine learning, natural language processing, web scraping, big data platforms, and data visualization techniques and their application to relevant public policy issues.
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machine learning data mining jobs Title: machine learning scientist in Mclean, VA
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