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Experience with machine learning related open source libraries including, but not limited to: Hadoop, Spark, SciKit-Learn, TensorFlow, etc. We are expanding in data science to provide the best information possible utilizing the latest techniques in Machine Learning (including Deep Learning, Neural network.
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Java, Python, ScalaExperience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence.
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Machine Learning and Deep Learning: Utilize machine learning frameworks (e.g., TensorFlow, PyTorch) to train and optimize NLP models. Hands-on experience in NLP algorithm development, machine learning, and deep learning for text analysis and processing.
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Qualifications We DesireMaster’s degree in Computational Biology, Computational Bioengineering, Machine Learning, Statistics, Computer Science, Mathematics, or a related field.
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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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Stay up-to-date with the latest advancements in data science, machine learning, and related fields, and apply them to improve existing processes and methodologies. Basic knowledge and experience in statistical and data mining techniques such as: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
$135,240 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Apply various Machine Learning (ML) and analytics techniques to develop classification and prediction models and leverage foundation models to develop generative AI capabilities; integrate client, domain (e.g., finance, sales) and industry knowledge into the solution.
$135,240 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Requirements: Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Engineering or related discipline. Sourcing and Spent OptimizationThe Role:You will help our clients navigate the complex world of modern AI, data science and analytics.
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Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Engineering or related discipline. You will help our clients navigate the complex world of modern AI, data science and analytics.
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Faculty research interests include algorithms and theory, AI and machine learning, bioinformatics, cyber-physical systems, computer networks, computer science education, computer vision and image processing, computational topology, data science, high performance computing, human computer interaction, open-source software, robotics and remote sensing, security and privacy, and software engineering.
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We are open to hiring candidates to work out of one of the following locations:Bellevue, WA, USABASIC QUALIFICATIONS- Ph. D. in Operations Research, Machine Learning, Statistics, Computer Science, Applied Mathematics, Operations Management, Industrial Engineering, Economics or a related field.
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Role / team focus areas could include supporting machine learning, deep learning, or quant initiatives across the enterprise. On any given day, you might:Evaluate open-source and internally-developed modeling and analytics tools using real business dataIntegrate internal data with external data sources and APIs to discover and implement actionable insightsDesign and craft data science models to communicate solutions to customers and company leadership We'd love to find someone who is.
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Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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The successful candidate will have a deep understanding of omni-channel principles/technologies, architecture patterns, and best practices, and experience with various technologies such as APIs, microservices, and cloud-based systems.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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