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Education RequiredHigh School or better PreferredBachelors or better s-p-m1 By applying, you consent to your information being transmitted by Monster to the Employer, as data controller, through the Employer’s data processor SonicJobs.
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The Information Technology and Applications Center (ITAC) of the National Heart, Lung, and Blood Institute (NHLBI), a component of the National Institutes of Health (NIH) at the Department of Health and Human Services (DHHS), is seeking exceptional candidates for the position of Data Science Architect (DSA.
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The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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We embed our deep content knowledge and methods expertise in our rigorous research, equity-focused practices, product development, mixed-methods evaluations, and technical assistance projects to benefit teaching and learning, often for learners who are traditionally underserved.
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GAI's team members work side by side with government IT executives and OEM partners to solve complex business problems such as AI/ML, RPA, Cyber Security, Big Data, Data Center & Cloud.
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Deliver on projects in the areas of data management, data governance, dashboard monitoring, DQ dashboards, data controls, data lineage, and data mapping. and Transformation (automation, machine learning, artificial intelligence, reporting.
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Our team is seeking a Senior Data Scientist / Machine Learning Expert with specialized experience in Generative AI and Large Language Models (LLMs), chatbots, and natural language processing to contribute to transformative projects for a government client within the Department of Homeland Security (DHS.
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Ability to design cloud architecture for an astrophysics data science platform using Kubernetes, as well as serverless computing such as Lambda, and serverless database services such as Athena. Ability to implement an astrophysics data science platform, making use of commercial cloud services such as AWS and Azure, as well as a locally managed public cloud with infrastructure leveraging Kubernetes, Docker, and Jupyter Hub.
$110,000 - $250,000 a yearFull-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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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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The Director is a senior professional who works in conjunction with the Vice President for Lifelong Learning, with additional coordination with the Rabbi, the Executive Director and other staff and lay leadership to create a unified and dynamic educational program.
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Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities. Deep Learning: Understanding neural networks, backpropagation, architectures like CNNs, RNNs, transformers, and tools like TensorFlow, PyTorch, or Keras.
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Expand your career at Pearson VUE in our Test Center Manager position foroursite located at Mason, OH (4770 Duke Dr. Pearson VUE is a business of Pearson, the world's leading learning company with global-reach and market-leading businesses.
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Experience in mathematics (statistics, linear algebra, differential calculus); data visualization (Tableau, Power BI, Qlikview); programming (SQL, Python, R, Java); data analysis (feature engineering, data wrangling, EDA) and machine learning (classification, regression, reinforcement learning, deep learning, clustering, dimensionality reduction.
$113,200 - $205,500 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Support USAID/BHA and other relevant partners in documenting learning, including designing methodologies and data tools, analyzing, and interpreting data, and writing up learning briefs, organizing webinars, or other knowledge dissemination modalities (stories, social media, videos etc.
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This role will examine industry trends, ticketing purchase history, athletic constituent behavior patterns, media engagement, and historic athletic donation data to drive business performance in the following verticals: Revenue associated with the Premium Seating, Ticketing, and Fundraising.
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data center deep learning jobs Title: engineer in Washington, DC
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