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The ideal candidate will be skilled in statistical analysis, machine learning, and leveraging Azure technologies in big data to drive significant business impact. Metas Solutions has an "immediate" opening for an experienced Data Scientist/Machine Learning Engineer to work Remotely.
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The initiatives will include both short-term and long-term research in areas such as artificial intelligence, machine learning & data mining, natural language processing, big data systems, information and data visualization, and social & cognitive science.
$199,300 - $247,500ExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Imagine harnessing the power of machine learning models, big data, and predictive analytics to transform the landscape of data center sustainability. Harness the latest advancements in Data Science, Machine Learning and Artificial Intelligence (AI) to pioneer new approaches that significantly help our sustainability objectives and drive efficiency across our data center operations.
$112,000 - $218,400 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Building these controls requires knowledge of big data techniques, ability to architect systems that can efficiently scale to hundreds of billions of data points per day, machine learning over unstructured and structured data, graph analytics, and experience with building UI for data rich applications.
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AWS Graviton powered instances provide the best price performance and support a wide range of computing workloads including application servers, microservices, high-performance computing (HPC), CPU-based machine learning (ML) inference, video encoding, electronic design automation, gaming, open-source databases, and in-memory caches.
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Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
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Responsible for the administration, configuration, and optimization of the Databricks platform to enable data analytics, machine learning, and data engineering activities within the organization.
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Hands on experience on Machine Learning, Artificial Intelligence, and/or Big Data. Leveraging innovative technologies such as machine learning and AI techniques to foster data analytical capability and support company growth strategy.
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The Expert Data Scientist will be a champion of the latest Machine Learning and Artificial Intelligence technology stack. Apply state-of-the-art algorithms relying on knowledge of statistical modeling, machine learning, and optimization to or improve the performance/quality of existing health propensities and related data products.
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MS in Computer Science, Information systems, or Computer engineering, Systems Engineering with relevant experience in Text Mining / Natural Language Processing (NLP) tools, Data sciences, Big Data and algorithms.
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Apply the current state of the art in big data, machine learning, and data science to business scenarios. Must have 3 years of experience in Advanced Machine Learning, Applied Statistics, and Artificial Intelligence, including demonstrated experience in Business Domain, risk management protocols, abstract requirements, early-stage issues/gaps identification, problem solving, concepts application, customer service, basic situation analysis, statistical modeling, computer programming, and software engineering.
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Title : Big Data Engineer. The position will work closely with the Team Lead, other Databricks Administrators, System Administrators, and Data Engineers/Scientists/Architects/Modelers/Analysts.
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Experience in machine learning, big data analytics, data science, and cloud computing is a plus. Qualified candidates need to be passionate about the Machine Learning and Artificial Intelligence space, will excel in problem-solving and combine an advanced business or technical degree with consulting or product management experience and have a record of successful delivery of complex, multi-faceted projects.
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This means that we want to continuously improve our method of doing Data Science / Machine Learning, and our knowledge of trends and techniques relevant to our areas. Collaborate to translate business requirements and objectives into problems that can be solved with a combination of data, statistics, and machine learning.
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Experience utilizing big data and machine learning technologies (e.g. H2O, Spark, Hadoop, Cassandra). Lead a team of 5-20 internal and external engineers (UI, Data Engineering, Machine Learning, and Backend.
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