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Perform evaluation of prototype, using EVs or real world big data of EVs. Work closely with other experts in Data Science, Optimization, Energy Systems, and Business to realize future service concepts of EVs.
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Hands-on experience with distributed systems such as Spark, Hadoop (HDFS, Hive, Presto, PySpark) to query and process data Experience with at least one major MPP (elastic map reduce) or cloud database technology (Snowflake, Redshift, Big Query) Experience with AWS Cloud technologies (S3 at a minimum) Solid experience with data integration toolsets (i.
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B. Job ResponsibilitiesHow you will be contributing:- Work closely with other experts in Data Science, Optimization, Energy Systems, and Business to realize future service concepts of EVs.- Develop and implement a cloud architecture for intelligent charging control of EVs.- Perform evaluation of prototype, using EVs or real world big data of EVs.- Communicate your work with stakeholders for business implementation.
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Your qualifications You have production experience with building and operating a DataLake, Data Warehouse or Data LakeHousesYou have a taste for big data streaming, storage and processing using open source technologiesYou can demonstrate your understanding of what it means to treat data as a productYou know what are Data Mashes and Data Fabrics and what is critical to make sure for them to bring valueYou are able to learn and adapt.
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Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
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Experience with Natural Language Processing: Java or Python, and ML, AI, Labeling, Annotation, Data Pipeline, Big Data, AWS, or Cloud Services. We’re on the lookout for the curious, those who think big and want to define the world of tomorrow.
$200,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Familiarity with CI/CD, ETL, big data tools, and mainstream ML libraries (e.g., MapReduce, Spark, Flink, Kafka, Docker, Kubernetes, TensorFlow, PyTorch, Spark ML, etc. As a machine learning platform engineer of the Samsung Ads Platform Intelligence (PI) team, you will have access to unique Samsung proprietary data to develop and deploy a wide spectrum of large-scale machine learning products with real-world impact.
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Experience with big data technologies (, Hadoop, Spark) and data warehousing solutions. Sr. Data Engineer - Kohler Ventures Work Mode: Hybrid Location: Hybrid - 3 days/week onsiteat Palo Alto, CA or New York City, NYOpportunityKohler Ventures is an independent company wholly owned by Kohler Co., global leader in the manufacture of kitchen and bath products, tile and home interiors, and an international host to award-winning hospitality and world-class golf destinations.
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Big plus if candidate has experience using Python, Power BI for data visualization. Highly prefer strong experience using DOE (JMP) and statistics for Data Analysis. Gathers operational and test data and evaluates results.
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We are seeking an experienced Big Data Software Engineer to design, develop and deliver next-generation technologies within our Prisma Access team. Familiarity in Big Data technologies like Hive, Kafka, Hadoop, SQL, developing APIs.
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Ford's GDI&A department is on the hunt for talented individuals skilled in Machine Learning, Big Data, Statistics, Econometrics, and Optimization. As part of our Global Data Insight & Analytics (GDI&A) team, you'll play a pivotal role.
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Microsoft’s Azure Data engineering team is leading the transformation of analytics in the world of data with products like databases, data integration, big data analytics, messaging & real-time analytics, and business intelligence.
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Strong experience in scripting/programming – Python, Java, PowerShell, Bash. Experience with configuration and management of SSO, Big Data/ No-SQL in cloud infrastructure. Experience with monitoring and log aggregation frameworks, such as Azure Monitor/Sentinel, Data Dog(preferred), Dynatrace, Elasticsearch, Kibana, Logstash.
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Work with BIG data, crunching millions of samples for statistical modeling, data mining, recommendation solutions. Experience in Big Data. Working knowledge in one or more of the following: machine learning, data mining, information retrieval, security data science, advanced statistics or natural language processing.
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Our award-winning software is powered by a team of world-class experts in big data, security, and scalable infrastructure. Summary As a platform engineer intern, you will learn how to build a next-generation machine learning platform, which incorporates our secret sauce, UML (unsupervised machine learning) with other SML (supervised machine learning) algorithms.
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big data jobs Title: engineer in Mountain View, CA
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