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Data science techniques such as predictive analytics, machine learning, natural language processing and business intelligence, including use of big and non-tabular data.
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Evaluate commercial and open-source techniques in Machine Learning, Data Mining, NLP, and Analytics. 6+ years of professional experience in NLP systems, predictive modeling, recommendations/personalization, clustering, classification, sentiment analysis, time series, and deep learning.
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The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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CUDA (Compute Unified Device Architecture) /OpenCL (Open Computing Language) Programming: Develop and optimize applications using CUDA or OpenCL, harnessing the full potential of GPU hardware for parallel processing, high-performance computing, and machine learning on Linux platforms.
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Experience with projects using Machine Learning, statistical methods, and natural language processing. You'll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality.
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The Python scripts will use supervised and unsupervised ML (both text and image-based machine learning), natural language processing (named entity extraction, summarization, etc.
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We are seeking a Senior Machine Learning Engineer who is an expert in Optical Character Recognition (OCR), Natural Language Processing (NLP), Large Language Models (LLMs), and other deep learning models.
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Applicants working at the boundary of computer science and related disciplines, including Computational Linguistics and Natural Language Processing, Robotics, and Scientific Computing are also encouraged to apply, and may be considered for joint positions with other departments or institutes on campus.
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Draw on deep technical knowledge and subject matter expertise to advise clients in multiple areas, including clinical psychology, psychiatry, neuroscience, and psychometrics, with an eye toward applications, such as digital mental health, psychological wellbeing, and predictive analytics and machine learning for personalized medicine and prevention.
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As a Farsi language-enabled Open Source Monitoring Specialist, you will use your Farsi language ability, Boolean logic, automated search tools, and other research skills to find potential threats in social media, news sites, forums, and other open source sources.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
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In this role, you will leverage your expertise in Python, Natural Language Processing (NLP) techniques, algorithms and statistics, as well as your familiarity with US Department of Defense mission needs, to deploy, optimize, and evaluate innovative machine learning and algorithmic solutions in client environments.
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Amida is currently looking for a Data Scientist to join our team in Washington, DC. In this role you will work across our client engagements, providing expertise in machine learning algorithms, natural language processing (NLP), data collection, data analysis, data mapping, data profiling, data mining, data modeling, and data visualization.
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Experience with deep learning, reinforcement learning, and natural language processing. The Natural Language Processing and Data Scientist’s responsibilities include: Developing NLP systems according to user and sponsor requirements.
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Linking millions of assured data points, Janes Open-Source Intelligence creates a framework of interconnected national security insights that allows our customers to better understand emerging threats, integrate all relevant data and connections into a single intelligence environment, and to deliver a more complete and accurate answer to their intelligence analysis.
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