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Seeking a Machine Learning Engineer with expertise in developing, deploying, and managing ML models using Google Cloud's Vertex AI. Google Cloud Professional Machine Learning Engineer certification is preferable.
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Apply knowledge of statistics and mathematical theory to develop and integrate new and emerging technologies, such as machine learning and deep learning concepts and techniques. The Department of Homeland Security (DHS) is recruiting professionals to support a range of developmental roles in Cybersecurity Data Science, including Data Scientist, Artificial Intelligence (AI) Specialist, AI Operationalization Analyst, Data Modeler, Data Security Analyst and Operations Research Analyst.
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Skilled with the use of open-source tools, cloud computing, machine learning, and data visualization. Experience in a data analytics, open-source tools, cloud computing, machine learning and data visualization.
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A deep understanding of data science and machine learning best practices, development processes, and leading platforms (Databricks, SAS, Anaconda, Alteryx, etc.) Experience in advanced analytics solutions (data science, machine learning, data modeling, etc.
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Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms. 3+ years using major machine learning/deep learning frameworks (e.g., Scikit-learn, PyTorch, TensorFlow and Keras) and algorithms (e.g., CNN, GAN, LSTM, RNN, XGBOOST.
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Familiarity with Databricks for data engineering tasks including ETL processes, data visualization, and machine learning. The ideal candidate will have a solid understanding of Java and Python programming languages, along with experience working with Databricks for data engineering tasks.
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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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You have familiarity with analytics like machine learning, natural language processing, or data visualization, particularly for creating tools that scale complex analytics workflows for less technical end users.
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Proving specialization background in data science, including experience with statistical analysis, data mining, predictive modeling, and machine learning; Demonstrating a thorough level of knowledge in statistical modeling, algorithms, data mining, and machine learning algorithms problem solving.
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Our high-performing team works with clients to implement the full spectrum of data analytics and data science, from data architecture and storage to data engineering and querying, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence.
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Coursework or thesis in machine learning, data mining, information retrieval, statistics or natural language processing. Experience with common machine learning techniques such as pre-processing data, training, evaluation of classification and regression models.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly. Infrastructure Support (IS) certification, including CEH, CySA+, GICSP, SSCP, CHFI, Experience with DevSecOps, CI and CD, IaC and CaC, IT Infrastructure Library, and IT.
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The Senior Staff Data Scientist for Beckman Coulter Diagnostics is responsible for research, design, and development of data science/machine learning solutions for Hematology related products.
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Assist ISSM/ISSO/ISSE with the Integration/Development new techniques to improve Confidentiality, Integrity, and Availability for networks/systems operating at various classification levels. Working knowledge of Local Area Network (LAN) and Wide Area Network (WAN) technologies and data backup technologies.
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Knowledge of Deep Learning and Machine Learning techniques, and experience in Machine Learning tools, techniques and programming (including LLM - Large Language Models) is a plus.
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