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Contribute research to top-tier NLP conferences such as Association for Computational Linguistics (ACL) and Empirical Methods in Natural Language Processing (EMNLP) You will work with a seasoned group of natural language processing (NLP), speech, and computer vision specialists, experimenting with emerging technologies in generative AI, delivering software implementing these technologies, and contributing research to major NLP and AI/ML conferences.
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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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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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Data Engineering skills to include:Experience with preparing data for analysisStrong understanding of data science conceptsExperience with BI tools Understanding ML frameworks, algorithms, and libraries.
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Advanced knowledge of advanced techniques such as: dimension reduction techniques, natural language processing, sentiment analysis, anomaly detection, geospatial analytics, etc. 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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7+ years of professional experience working on complex data challenges in the areas of data architecture and engineering, data science, data analysis and visualization, machine learning, artificial intelligence, or related discipline.
$82,100 - $172,400 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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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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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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.
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Data Techniques: Advanced knowledge of techniques like dimension reduction, natural language processing, sentiment analysis, anomaly detection, and geospatial analytics. The ideal candidate will 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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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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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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One or more certifications: OCI Associate Architect, OCI Architect Professional, AWS Certifications: AWS Solutions Architect, AWS Security Specialist, Microsoft Certified: Azure Security Engineer, Associate, Microsoft Certified: Azure Solutions Architect, GCP Cloud Architect Certification, Oracle Database, CompTIA Security +, ISC/2 CISSP.
$137,900 - $232,300 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Full Stack Development experience, including experience with Python, Django web applications, REACT web applications or other Javascript frameworks, RESTful API architecture, and incorporating machine learning models into web apps.
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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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