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Coursework or work experience applying predictive modeling techniques from data science, statistics, machine learning, and econometrics to large data sets. Qualifying coursework may include—but is not limited to—data science, statistics, machine learning, optimization, numerical analysis, scientific programming, computational methods, supervised learning, unsupervised learning, text mining, and image analysis.
$118,000 - $178,000 a yearFull-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. We are seeking Full Stack Software Engineers who are passionate about marrying data with emerging technologies.
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Linux, Robot Operating System (ROS), machine learning/vision, and topics in autonomous robotics including perception, sensor fusion, SLAM, localization, and autonomous navigation. Experience in one or more of programming, machine learning, Robot Operating System (ROS), Computer Aided Design (CAD), and robotics is recommended.
$22 - $36 an hourInternExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Net, C#, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Python, Data Modeling, SQL, SSIS, SSAS, SSRS, Power Automate, Power Platform, AI Builder, Power Apps, Blue Prism, Automation Anywhere, UiPath Studio, Orchestrator, ERP, QuickBooks, SAP, NetSuite, Oracle, API, JSON, XML, Web Services, SOAP, Postman, Fiddler, Integration, Custom Activities, DLL, Insight, Automation Hub, Task Capture.
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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy.
Full-timeRemoteExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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AWS DevOps Engineer, Solutions Architect, or SysOps Administrator. We are currently seeking a Data Scientist- SME to join our team. Demonstrated experience with geo-spatial software and programming packages and data formats.
$230,000 - $242,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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The Director of Ontology and Data Modeling will be responsible for partnering with Technology, Machine Learning, and other Capital One teams to support the development and integration of semantic technology into Capital One products and services.
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Develops solutions that support artificial intelligence, machine learning, and deep learning to facilitate dynamic automated signal development processes, that include recognition and exploitation.
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We are a leader in providing software engineering, big data analytics and visualization, artificial intelligence and machine learning solutions, DevSecOps, data center operations support, and cloud migration for our law enforcement and national security customers.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Partner with Corporate HRBPs, Global Talent COE, Learning and EI&D COE to take the data provided on succession planning and functional talent pool planning and drive relevant segment and x-segment insights and initiatives.
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PureSoftware is a global software products and digital services company that focuses on driving a differentiated customer experience, accelerating cycle time and improving business outcomes through an integration of digital solutions, robotic process automation, artificial intelligence, machine learning and IoT. Our solutions leverage next generation disruptive technologies to deliver competitive advantage to your business.
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The areas include but are not limited to machine translation, translation memory, information extraction, name-matching, speech/audio processing, document exploitation, and evaluation. Preferred Qualifications Bachelor’s or Master’s preferred in computational linguistics, artificial intelligence, computer science, or mathematics.
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It leverages technologies like robotic process automation (RPA), machine learning, natural language processing, and blockchain to help its clients enhance operational efficiency, improve customer experience, and drive business growth.
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Hands-on experience with machine learning (including deep learning and reinforcement learning), and one or more of the following technical areas: large language models (LLM), generative AI, decision science, human machine teaming, cognitive science, AI testing and evaluation, multi-agent systems, knowledge-based reasoning, automated planning, semantics, and ontologies.
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Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc.
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