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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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BRMi is seeking a Senior Data Scientist to provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for Compliance-Complaints.
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Experience with artificial intelligence, large language models, machine learning, and natural language processing techniques. Demonstrated expertise in one or more areas of data management, data science, and/or data engineering.
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Master's degree or PhD in computer science, data science, systems engineering, software engineering, engineering, or information systems. We are in search of candidates with a robust background in both data engineering and data management, coupled with an unwavering commitment to harnessing data for informed decision-making and critical mission processes.
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Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for Compliance-Complaints.
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As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Amazon has been investing in Machine Learning for decades, and by joining AWS you’ll join a community of scientists and engineers developing leading edge solutions for enterprise-scale data science applications.
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2+ years of experience working with modern AI capabilities in machine learning, including deep learning and natural language processing, and LLM frameworks. 5+ years of experience with artificial intelligence, data science, ML engineering, data research, or data analytics.
$125,600 - $285,000 a yearFull-timeExpandUpdated 1 month ago - UpvoteDownvoteShare Job
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The Oracle Government Defense & Intelligence (GDI) Cloud Adoption Engineer position, a member of the Cloud Solution Engineering job family, is a highly visible and influential individual contributor role.
$137,900 - $232,300 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Focused experience in artificial intelligence (AI), including machine learning and natural language processing (NLP) Skilled in documentation and database reporting for the purposes of analysis, data discovery, and decision-making with the use of relevant software such as Crystal Reports, Excel, or SSRS.
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These engagements will focus on Real Time and Batch-based Big Data processing, integration and governance, Business Intelligence, Visualizations, data science and Machine Learning.
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Capture and share best-practice knowledge amongst the worldwide AWS solution architect community. In this technical role focusing on Data Analytics and ML, you will architect enterprise-grade AWS solutions, own the technical relationships and deliverables for a GSI, develop and execute multi-day workshops, lead white boarding sessions, author white papers and blog posts, and respond to complex technical inquiries including RFPs. You will partner with Sales, Business Development and the Data & Analytics Service teams to enable partner’s Data & Analytics services adoption.
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A certification such as Red Hat Certified Engineer, Puppet Certified Professional, AWS Certified Solution Architect, Certified Kubernetes Administrator (CKA), or Docker Certified Associate (DCA.
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Integrate and leverage open-source tools to efficiently orchestrate complex digital signal processing algorithms, comprehensively visualize processing results and system configuration, and or aggregate processing results for further innovative analysis and data discovery.
$102,900 - $216,200 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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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