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MS/PhD in Electrical Engineering, Statistics, Bioinformatics, Computational Biology, Computer Science, Mathematics, or equivalent practical experience. 5+ years of experience in data analysis or related fields such as Data Scientist, Computational Biologist, or.
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Experience with commercial/ industrial electrical systems, hydraulic and pneumatic equipment and connections. Verifiable experience in electrical wiring processes, electronics, control systems, AC/DC or training in similar fields.
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Expert understanding of the electrical and mechanical systems used in a data center environment, including, but not limited to the following: electrical distribution and layout, Transformers, PLC’s, Generators, Switchgear, UPS systems, STS’, ATS’ PDU’s, Chilled Water Systems, CRAC/CRAH’s, Pre-Action Sprinkler Systems.
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The team tackles problems of massive scale, with a critical data footprint that has bottomline business impact, resiliency & availability requiring the best techniques within Big Data Analytics and Machine Learning, all while providing a superior analyst experience on our tools.
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We provide engineering services for green hydrogen production via electrolysis using solar, wind, hydro, and nuclear power sources and we support on-site usage in power generation, fuel cells, and fueling stations.
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The product manager will also work with an engineering team that develops Empowerly APIs using Node and Express, managing our Messaging Service in TypeScript, and contributing to Machine Learning workflows with Python.
$80,000 - $110,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Demonstrated proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis,DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB) and modern data warehouse tools including Snowflake and DataBricks.
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As the Chief Electrical Engineer with Sciaky, you will be responsible for leading the electrical and controls design team for Sciaky products in a cost effective manner, following our Quality Management Systems to assure compliance with standards and specifications.
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Bachelor's Degree in Science, Mathematics, Mechanical and/or Electrical Engineering, or a related field in Data Analytics. Strong knowledge and understanding of operations, maintenance, and electrical systems, applicable to wind and/or solar-storage power technology.
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Advanced proficiency in the design and implementation of modern data architectures and concepts such as cloud services (e.g., AWS, Azure, GCP), real-time data distribution (e.g., Kafka, Kinesis,DataFlow, Airflow), NoSQL (e.g., MongoDB, DynamoDB, HBase, CosmosDB) and modern data warehouse tools including Snowflake and DataBricks.
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Innovation: Focus on the development and application of new methodologies, technologies, and techniques to gather data and insights including Machine learning AI, Mobile Optimized Surveys, Gamification, Behavioral economics, real-time feedback, Multimodal surveys, Blockchain technology, Virtual and Augmented reality.
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We expect our Machine Learning Engineer to have excellent skills with Python and its machine learning / natural language processing libraries, and have working experience with both structured and unstructured data.
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Candidate will be familiar with various basic manufacturing processes, including machining, stamping, and injection molding, as well as data analytics and process improvement techniques such as Lean and Six Sigma.
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United Airlines is seeking dedicated professionals to join the Data and Machine Learning Engineering team. Stay aligned with the latest developments in cloud-native and ML ops/engineering and to experiment with and learn new technologies - NumPy, data science packages like sci-kit, microservices architecture.
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Merkle's expertise has earned recognition as a "Leader" by top industry analyst firms, in categories such as digital transformation and commerce, experience design, engineering and technology integration, digital marketing, data science, CRM and loyalty, and customer data management.
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