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Deep understanding of emerging technologies, data analytics, cloud architectures, cybersecurity best practices, and a keen understanding of disruptive technologies including artificial intelligence, machine learning, and quantum computing, and their potential applications within the Intelligence Community.
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Bachelor's degree in a quantitative or technical field of study (e.g. Applied Mathematics-probability and statistics, formal modeling, computational social sciences, Computer Programming-programming languages, math/statistics packages, computer science, machine learning, scientific computing, and Visualization (e.g. GIS/geospatial analysis, telemetry analysis.
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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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Proficiency in data analysis tools (Python, R), machine learning frameworks (TensorFlow, PyTorch), and data visualization tools (Tableau, Power BI). As a Healthcare IT Data Scientist, you will play a vital role in leveraging data analytics and machine learning to drive actionable insights and innovations that enhance patient care, improve healthcare operations, and support strategic decision-making.
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Emerging Technologies Group: Covers a wide range of work including Internet of Things (IoT) penetration testing, intelligent automation, artificial intelligence/machine learning and quantum computing.
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Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, including Data Science and Machine Learning. where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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Develop and publish relevant bioinformatics methodologies, pipelines, and algorithms, and stay abreast of the latest advancements in bioinformatics, machine learning, and oncology research.
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PhD in Computer Sciences, Electrical Engineering, or Mathematics with specialization in machine learning, deep learning, or natural language processing. We are looking for a passionate, talented, and resourceful Senior Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas.
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As the Data Scientist, your skillset will create useful and actionable insight for the customer through the development of machine learning, deep learning models, and related algorithms.
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As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
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The Anti-Money Laundering Modeling and Advanced Data Insights team is on a journey to modernize the way Capital One identifies potential money laundering, terrorist financing, and human trafficking through the use of machine learning, statistics, and other advanced analytic techniques.
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Evaluate commercial and open-source techniques in Machine Learning, Data Mining, NLP, and Analytics. Master's degree in Computer Science, Statistics, or Mathematics required with emphasis on data mining, NLP, or machine learning.
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Experience in R, Python or similar applicable programming languages, with some experience utilizing Artificial Intelligence (AI) and Machine Learning (ML) tools and techniques. SAIC is seeking a mid to senior level Electrical Engineer with a passion for electrical design methods, electrical CAD tools, and Digital Engineering interests to join our energized Engineering Innovation Factory Team of solution architects, digital engineers, and core engineers to define and build the infrastructure that fuels the Digital Engineering Transformation across our entire industry.
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We are a multidisciplinary team with expertise in machine learning, data engineering, and software development. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Mgr, Machine Learning Engineering.
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Coursework or work experience applying predictive modeling techniques from data science, statistics, machine learning, and econometrics to large data sets. Qualifying coursework may include—but is not limited to—data science, statistics, machine learning, optimization, numerical analysis, scientific programming, computational methods, supervised learning, unsupervised learning, text mining, and image analysis.
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machine learning jobs Title: electrical engineer in Mclean, VA
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