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Experience with one or more of the following: Machine Learning, Deep Learning, NLP, ranking systems, recommendation systems, backend, large-scale systems, data science, full-stack.
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They will use relevant statistical techniques, machine learning models and artificial intelligence algorithms to analyze data, design data models and derive insights to influence actions that maximize business value and effectiveness for the commercial technology segments.
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The position of Data Scientist will attend to all stages of data science projects utilizing technologies and tools such as Deep Learning, Traditional Machine Learning, and advanced analytical tools.
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Earned graduate degree (Ph. D. or M.Sc. + 2 years relevant industry experience) in a highly quantitative discipline (e.g., machine learning, statistics, computer science, applied mathematics, theoretical physics, physical chemistry, econometrics, bioinformatics.
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Develop image processing algorithms for Electro-Optical/Infrared (EO/IR) or Hyperspectral Imagery (HSI) data. You will develop image processing algorithms, architect all links in the signal processing chain, guide a team of developers, and validate system performance on a variety of modeling and simulation platforms.
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Data Scientists contribute to projects involving one or more of the following disciplines: Data Science, Applied or Theoretical Machine Learning, Deep Learning, Deep Reinforcement Learning, Physics Inspired ML, Classification Systems, Natural Language Processing, Artificial Intelligence, or Computer Vision.
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Hands-on experience with analytics and big data technologies within Microsoft Azure, with experiences in tools such as Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks and Azure Synapse Analytics.
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Causal modeling, NLP, time series, deep learning, etc. Develop and Enhance ML Models: You’ll design, build and deploy sophisticated machine learning models that improve our credit decisioning, fraud detection and other processes.
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Incorporate machine learning, statistical modeling, visualization and analytics tools and data sources into the development of processes and techniques to use data effectively and efficiently.
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Perform fluid flow path design, data analyses, computational fluid dynamics (CFD), and optimization analyses, including modeling and analysis of thermodynamic systems for power generation, waste heat recovery, and cooling.
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Keywords: Senior Environmental Planner, NEPA, Environmental Impact Analysis Proces, EIA, Air Force, DoD, airspace modeling, military aircraft noise modeling. Proven experience working on airspace issues and FAA NEPA, airspace modeling, and military aircraft noise modeling.
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Late Dr Rahul Balusu was the one who taught us computational linguistics/NLP. I was fascinated by howlanguage could be morphed into algorithms that simulated “language understanding” in machines.
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Leveraging computational fluid dynamics (CFD), wind tunnel testing, reduced order modeling, and flight data, we take a proactive approach to supporting cross-disciplinary design initiatives.
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The IT Program Manager I must have expert level skills in Data Warehousing and BI architecture such as the ETL process, dimensional modeling, OLAP, and Dashboards. Experience with reporting systems and data warehouse requirements gathering, analysis and design of ETL processes using SQL Server Integration Services (SSIS.
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Artificial Intelligence, Machine Learning, Cybersecurity, Data Security, Security Analytics, Network Security, Identity and Access Management, IT Risk Management, Behavioral Analytics. It leverages machine learning behavior profiling with predictive risk-scoring algorithms to predict, detect and prevent data breaches, fraud and insider threats.
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