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Coursework at the graduate or undergraduate level in artificial intelligence, virtual reality, machine learning, natural language processing, blockchain, and/or bioinformatics.
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Knowledge of advanced statistical methods and/or Machine Learning, Artificial Intelligence, and Natural language Processing in business use-cases. A Bachelor’s degree or above in Statistics, Computer Science, Quantitative Finance, or other STEM related field.
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Application of Data Science in Marketing: Apply data science techniques to complex marketing problems including customer segmentation, predictive modeling, pricing strategy, customer experience enhancement, and more.
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Performing and leading developments using machine learning techniques in one or more of the key areas like information retrieval and ranking, natural language processing, computer vision, entity recognition, and product classification.
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Key Responsibilities: Lead Data Science Projects: Design, develop, and implement predictive modeling projects that address critical business problems, leveraging expertise in machine learning, deep learning, natural language processing, generative AI, and other areas.
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Committees may include topics such as AI/machine learning, ethics, natural language processing, data definitions, data governance, genomic/pathology/radiology and other specialized clinical data systems, Epic, internal and external data reuse, learning health systems and translational science.
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The Communications Surveillance Vice President role will report to the Lead of Transformation, Audit and Reporting within the Compliance Communications Surveillance function and will be instrumental in developing, deploying, and maintaining Natural Language Processing (NLP) and other model-based capabilities for the Communications Surveillance Program.
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Bachelor's degree or equivalent required, preferred college courses in Digital Forensic Science, Computer Science/ Engineering, Computer Information Systems, Mathematics, Criminal Justice, or a related field and two or more years work experience in computer hardware, network administration, or cyber-crime investigations.
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We are growing our capabilities using artificial intelligence, natural language processing and machine learning. Providing input into initiatives to continuously improve straight through processing (STP) rates, including the use of robotics, workflow and other innovative re-engineering techniques.
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The Bedrock AI Data Team in Amazon Web Services (AWS) is looking for a Language Data Scientist to collaborate in developing solutions for natural language data collections. You will collaborate with fellow language data scientists, program managers, as well as stakeholders in science, engineering, and product teams to understand the role data plays in developing models that meet customer needs.
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You will provide a range of qualitative and quantitative consulting services in the areas of data science, AI, model development, model validation, model risk management, modeling technology, model governance / controls / documentation, and financial instrument valuation.
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Machine Learning and Statistics : A fundamental understanding of machine learning and statistical concepts to enhance data analysis, including basic predictive modeling and classification techniques, while also aiding in identifying data nuances for more effective Exploratory Data Analysis (EDA) is a plus.
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As a part of our team, you will solve intriguing problems in the domains of machine learning, information retrieval and ranking, natural language processing, and computer vision.
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Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms; Analyzing Conversational (Chats, Emails, Messages and Calls) data, and the use of this data to build Natural Language (NLP) modeling pipelines for intent classification, training & deploying conversational AI systems, IVR, virtual assistants, chatbots etc.
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Key Responsibilities: Develop and manage IVR and chatbot solutions, natural language understanding (NLU) systems and grammars. Utilize web services, APIs, and other communication protocols to integrate IVR systems with other computer systems (e.g., SOAP, VXML, SQL, XML, REST.
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