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Vice President of Research ( VPR ) seeks to hire a Natural Language Processing ( NLP ) and Data Scientist. Experience with deep learning, reinforcement learning, and natural language processing.
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Leverage your expertise in Natural Language Processing (NLP), computer vision, and machine learning to develop and implement models that will drive strategic decision-making. Develop and maintain robust data processing pipelines, databases, and APIs to support the company's product needs.
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The Data & Analytics department in Legal and Compliance is responsible for designing and optimizing surveillance models, approaches and tools using advanced analytical techniques like supervised and unsupervised machine learning, Natural Language Processing (NLP) and evolving techniques like reinforcement and deep learning as well as graph analytics.
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Experience in Natural language processing (NLP), Prompt engineering, Embedding, Vector DB. BigQuery, AI Platform, TensorFlow Extended (TFX), Dataflow, and Compute Engine. Experience in Natural language processing (NLP), Prompt engineering, Embedding, Vector DB.
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In-depth knowledge of AI technologies, such as machine learning, natural language processing, computer vision, and deep learning. We help organizations like Uber, GoDaddy, MGM, Siemens, Stanford University, and the State of California, build distributed software development teams, and deliver transformational digital solutions.
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Our client is seeking a Technical Product Owner to help drive the tactical execution of a Natural Language Processing (NLP) Data Infrastructure for the Department of Veteran's Affairs.
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Experience with Natural Language Processing (NLP) to automatically create service tickets in Service Now from an outlook mail account. Work with the Data Science team to bring machine learning Analytics models into production including building and running Big Data processing pipelines.
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Prior experience working with data science, machine learning, or natural language processing. Prior experience working with container-based technologies such as Docker, Kubernetes, and OpenShift.
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Knowledge and experience of emerging technologies such as machine learning (ML), artificial intelligence (AI), natural language processing (NLP), UI/UX, Python, and business intelligence tools such as Tableau.
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Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data- oriented programming languages (Python, R) and visualization software such as Tableau, Teamcenter Reporting and Analysis (TcRA), Cognos and Informatica.
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7+ years experience with core analytic methodologies (e.g. regression, classification, clustering, matrix factorization, natural language processing, decision trees, support vector machines, neural networks.
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Certifications/licenses: Machine Learning and Natural Language Processing. Bachelor's degree in Computer Science, Computer Programming and Data Processing, Computer and Information Systems, or Information Sciences.
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Experience with application areas of machine learning, including computer vision, natural language processing, and learning on graphs. You'll design and implement machine learning solutions for complex tasks on large datasets, including extracting insights from multiple disparate data sources and types, such as cyber, language, and vision.
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Experience with IBM AI Fairness 360 (AIF360) – preference; Machine Learning (ML); Natural Language Processing (NLP); spaCy and NLTK, as well as language models like BERT and RoBERTa, are desired.
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Thomson Reuters Labs in Toronto is seeking scientists with a passion for solving problems using state-of-the-art Information Retrieval, Natural Language Processing and Machine Learning.
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