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Through this research experience, the fellow will have the opportunity to explore earth science community standards for the intake and publication of gridded data sets; contribute to the conversion of data holdings to cloud-optimized formats; and develop documentation of best practices for the handling of big datasets.
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Big Data Technologies:Distributed Computing: Tools like Apache Spark, Hadoop. Big Data Storage: Technologies such as HDFS, Apache Cassandra, or cloud storage solutions. Software Engineering & DevOps:Version Control: Familiarity with tools like Git. Continuous Integration/Continuous Deployment: Knowledge of pipelines and tools like Jenkins, Travis CI. Containerization: Familiarity with Docker, Kubernetes, etc., for scalable deployment of data science applications.
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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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Familiarity with using cloud services (AWS, Google, Azure) or Big Data tools (Hadoop, Hive, Spark) in data science solutions. Demonstrable knowledge in artificial intelligence, machine learning, data science, and other relevant technical domains; and possess a blend of advanced analytical capabilities and consulting expertise that will create value and insights for our clients.
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Big data” doesn’t faze you. 11 West 19th Street (22008), United States of America, New York, New YorkManager, Data Science - Fraud, Deep Learning. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
$229,900 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Manager, Data Science - Fraud, Deep Learning. The Fraud Data Science team builds the machine learning models that help protect our customers and Capital One against fraudsters.
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Technical: You have hands-on experience developing data science solutions from concept to production using open source tools and modern cloud computing platforms. San Francisco, California (Hybrid On-site): $213,400 - $243,500 for Manager, Data Science.
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Innovation is at the heart of everything we do at the Audit Analytics and Innovation Team. We’re not a traditional Data Science team: we build creative ML solutions across multiple domains from LLM based chatbots, GenAI powered applications, to AML/Fraud solutions, Card statements anomaly detection, Customer call transcripts intelligence, etc.
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Job Description Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities.
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Object-oriented coding experience and shell scriptingInfrastructure knowledge:Linux systemsVirtualizationDockerKubernetesCloud (AWS/Azure/GCP)Experience in building solutions with Big Data tools and frameworks, some of:SQL DBsSpark, Hadoop, Cassandra, Redis, Mongo, Elastic.
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Center 2 (19050), United States of America, McLean, VirginiaSenior Associate, Data Science - Retail Bank. You know understanding the data is often the key to great data science.
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They also use and advise on such tools as machine learning, natural language processing, web scraping, big data platforms, and data visualization techniques and their application to relevant public policy issues.
$57,800 - $79,086 a yearFull-timeExpandApply NowActive JobUpdated 29 days ago - UpvoteDownvoteShare Job
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The Sr. Data Science Analyst will manage, architect and analyze big data in order to build data driven insights and high impact data models. The Sr. Data Science Analyst supports the development and maintenance of business intelligence solutions and analytics products.
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3+ years of data engineering experience with modern big data analytics architectures (Hadoop, SQL, HIVE, Spark, Snowflake, etc.) The SOPAX Data Science team consists of highly skilled Data Scientists working together following an agile methodology and design thinking.
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Having experts in a wide variety of domains (software architecture, big data & cloud computing, aviation domain, etc.) Experience with data science, analysis, modeling, and visualization using Python, R, and/or Clojure.
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big data jobs Title: data science in Mclean, VA
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