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Transform your career to the next level with GDIT as a Solutions Architect 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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As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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You name it) and environments (big data [petabytes], machine learning, multiple clouds) serve more users than almost any other US Government Agency according to. NCBI's wide range of applications, platforms (node, python, Django, C.
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The Fraud Data Science team builds the machine learning models that help protect our customers and Capital One against fraudsters. Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, Pytorch, Tensorflow and more — to reveal the insights hidden within huge volumes of numeric and textual data.
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If playing a key role in Single-Family’s Innovation, Data Engineering and Analytics (IDEA) Transformation journey and using state of the art techniques such as Machine Learning and Artificial Intelligence and Big Data/Cloud Technologies excites you, you should apply now and learn why there’s #MoreAtFreddieMac.
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This position sits within the Data & Machine Learning domain, emphasizing an automation mindset where coding skills translate across various tasks, particularly Python-based and batch applications.
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Our group is responsible for developing core solutions in data mining, machine learning, anomaly detection and natural language processing, positively impacting multiple existing Extreme flagship products and new offerings from the company.
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3-5 years of design and development experience in advanced analytics including machine learning, artificial intelligence, and statistical computations in Python and R. Experience with supervised and unsupervised learning, Natural Language Processing, and data augmentation to address imbalanced training sets.
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Assist with machine learning and data visualization initiatives as needed. Strong background in a modern programming language, such as Python or Java, with at least 4 years of experience working in a big data and cloud environment.
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Stay updated on the latest advancements in data science, machine learning, and artificial intelligence. Experience working with Amazon Redshift and Spark for big data analytics.
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Significant experience using Python, including use of modern data science and machine learning packages and frameworks (Java, c. Experience building and optimizing data pipelines, including big data tools with Spark, Kafka.
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Organization delivers exceptional technology, products, services and processes to support our Data and Machine Learning ecosystems and core functions that support holistic operations for Capital One as an enterprise.
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Extensive experience with Azure Data services (Azure Data Lake, Azure Data Factory, Azure SQL Data Warehouse, Data Lake Analytics, HDInsight, Machine Learning, and Stream Analytics.
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Experience with big data analytics, machine learning, artifi cia l intelligence, or anomaly detection. Experience with scripting in PowerShell and BASH command line interfaces, or Python or Perl scripting languages.
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Based on a white paper written by our client's CTO, the Agency's top Machine Learning Chief has provided funding to apply Artificial Intelligence to a dozen years of data coming from six different sources.
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