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Emerging Technologies Group: Covers a wide range of work including Internet of Things (IoT) penetration testing, intelligent automation, artificial intelligence/machine learning and quantum computing.
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Amida is currently looking for a Data Engineer to join our team in Washington, DC. In this role you will work across our client engagements, providing expertise in machine learning algorithms, natural language processing (NLP), data collection, data analysis, data mapping, data profiling, data mining, data modeling, and data visualization.
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Software Engineering, Intelligence Community, Java EE, Amazon AWS Consulting Partner, GSA Schedule, Microsoft Partner, Cross Domain Solutions, Business Automation, Business Intelligence, Artificial Intelligence & Machine Learning, Content Management, and Integrated Data Management.
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Utilization of artificial intelligence and machine learning tools (including LLMs) to transform large and complex financial datasets and analyze datasets to provide insights that can help drive business decisions.
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Knowledge and experience using programming languages (R, Python, SQL) and data tools (Excel, Google Sheets) in a data analysis, machine learning, or data science capacity. Specialist in Business Intelligence Tools: (Tableau, Power BI, Metabase, etc.
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Knowledge, skills, and relevant experience in one or more of the following is required: - Designing and implementing machine learning - Data mining - Advanced analytical algorithms - Programming - Data science - Advanced statistical analysis - Artificial Intelligence - Computational science - Software engineering - Data engineering.
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The role will reside in the Washington, DC office with hybrid work capabilities and will beresponsible for designing, developing, and deploying AI/ML-based (Artificial Intelligence/Machine Learning) models and Generative AI solutions, to support and enhance our legal and business services operations.
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Provide technical excellence to apply state-of-the-art machine learning / artificial intelligence utilizing technologies such as Spark, R, Hadoop, Scala, SQL to real world infrastructure business problems.
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We integrate threat intelligence, event monitoring, security analytics and incident response, while catalyzing machine learning and automation orchestration to detect targeted cyberattacks.
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The team is comprised of the best-in-class technology partners to leverage forward-leaning technologies and best practices to transform GSA's IT capabilities and shift offerings to provide a more flexible service delivery model, completing the agency's shift to a fully digital experience along with its adoption of advanced, emerging technologies such as intelligent automation, artificial intelligence, and machine learning.
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ALQIMI’s RAAVNapplication is used by the USAF & JPEO to detect Integrated Early Warnings related to CBRND threats around the world analyzing unstructured, publicly available data using machine learning- and statistical based anomaly detection.
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In addition, Dalet solutions increasingly include state of the art technologies such as Cloud architectures, Business Intelligence, Data Analytics and Machine Learning Configuring, testing and troubleshooting solutions based on those technologies.
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2-4 years of experience developing Machine Learning Applications in Python using popular Machine Learning and Data Science packages and frameworks such as Keras, Scikit-learn, Pandas, PyTorch, Flask etc.
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Minimum 2+ years experience with Databricks for data pipelines, models and data science development Minimum 1+ years experience working with graph databases such as Neo4J, AWS Neptune or others Exposure to Tableau, PowerBI, and/or SAS Viya business intelligence tools Ability to effectively communicate in writing and orally with a wide range of audiences and maintain interpersonal relationships.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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machine learning business intelligence jobs in Washington, Kenmore, Washington
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