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Oversee and direct robotic automation efforts including the identification of automation opportunities, assess automation feasibility and benefits, and the use and determination of which robotic automation technology(ies) (Robotic Process Automation (RPA), Artificial Intelligence (AI), and Machine Learning (ML) would meet business outcome(s.
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Validating and training AI machine learning models with annotated training sets in tuning accuracy of the AI models for CLM use cases;Demonstrating knowledge of machine learning and artificial intelligence workloads and considerations on Azure;Demonstrating knowledge of Azure Blob storage, Azure Service Bus and Azure Key Vault cryptography;Designing solutions for custom applications using the Microsoft.
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Contact Center Solutions: Fueled by cloud based artificial intelligence and machine learning, we implement next generation contact center solutions, purpose built for each client. We achieve these goals by leveraging industry leading cloud based artificial intelligence and machine learning technologies.
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The ideal candidate will have a deep understanding of artificial intelligence, machine learning, and data science, coupled with a strong background in Pre-Sales Solution Architecture. Understanding of AWS, Azure, and/or Google Cloud Machine Learning Services.
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Become an expert in all areas of development within our graph data team and work on cross-functional projects including Natural Language Processing, Machine Learning, and AI techniques driven from our cutting edge platform.
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Experience in understanding business issues of large CSP, accelerated Computing/ Data Center technology/ Deep learning & machine learning. Experience with deep learning, data science, and NVIDIA GPUs.
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Develop an automated system for detecting anomalous behavior within the DHHS cloud environment using machine learning algorithms. CISSP / CISA / CCSP / Any security specialty certification on one of the leading cloud platforms (AWS/Azure/GCP.
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Experience reviewing Soc2 Type2, FedRamp, HITRUST compliance reports. Conduct penetration testing on the DHHS cloud infrastructure, identifying vulnerabilities in its security systems. Experience in Cloud Security Security architecture to ensure the department is meeting the federal, state, department and industry best practices.
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Strategic Thinking: Ability to craft and execute a data strategy that integrates data analytics, data science, and machine learning to support business objectives and foster innovation. Technical Skills: Proficiency in SQL, database platforms (e.g., MySQL, Oracle, SQL Server), data warehousing, ETL processes, data modeling tools, and familiarity with cloud services (AWS, Azure, Google Cloud), big data technologies (Hadoop, Spark), and data pipeline tools (Apache Kafka, NiFi.
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We optimize our clients’ experience using unique proprietary technology coupled with robotic process automation, intuitive digital programs powered by machine learning, and enhanced by an extensive proprietary transaction data set.
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Demonstrate proficient experience with machine learning algorithms, including deep learning, gradient boosting, and random forestsPossess advanced programming skills in Python, R, or other relevant languages for data analysis.
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Js for User Interface (UI) developmentKnowledge of Python, Spark, Hadoop, Big data, and science for anomaly detection using machine learning and statistical risk modelsExtensive experience with databases (including Oracle or Structured Query Language (SQL.
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Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types.
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We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation.
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This role will be responsible for strategic planning of Machine Learning initiatives with the Product, Engineering, Performance and Business Intelligence teams, analysis of potential impact and prioritization of those projects.
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