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In supporting rule analysis, Teammate should be able to Independently perform sophisticated data analytics that fit to the fraud problem being observed (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data.
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We are interested in a variety of topics including large-scale distributed systems, stream processing, edge computing, applied machine learning and AI, big graphs, natural language processing, big data management, and heterogenous data analytics.
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The Sr. Lead, Internal Audit Data Scientist will use advanced analytics, machine learning, and data visualization techniques to address some of Rivian’s most significant and most complex risks.
$239,000 a yearFull-timeExpandApply NowActive JobUpdated 28 days ago - UpvoteDownvoteShare Job
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Python, Data science, Machine learning, Data, Sql, Erpss, Predictive modelling, Algorithm, Statistics, Daiss, Data analysis, Predictive analytics, Artificial intelligence, Azure, Modeling, Cloud.
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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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Experience or interest in data science, machine learning, artificial intelligence, wireless communications, sensors, semiconductors, Internet of Things, Ior related fields. Receive training and development that could lead to becoming a licensed patent agent by the United States Patent and Trademark Office (USPTO.
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Motivated individuals who are looking for a career path to becoming a licensed patent agent with the United States Patent and Trademark Office (USPTO). Patent Specialist - IP PatentsLocation: Atlanta, GA | Charlotte, NCAn AmLaw 50 international law firm's Intellectual Property – Patents Group is looking for a Patent Specialist with a background in computer science or electrical engineering.
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Comprehensive benefits package, including medical, dental, vision insurance, 401(k) plan, personal medical and parental leave, paid holidays, dependent care, elder care, concierge services, financial and physical well-being, and personal health advocacy programs, and various corporate discounts.
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Candidate Profile: Bachelor’s Degree or higher in Electrical Engineering, Computer Engineering, or Computer Science is preferred. Opportunity to join a leading Intellectual Property team at a top national law firm.
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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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Experience with AirFlow, Beam, Spark, BigQuery and other cloud based and distributed technologies to scale machine learning models and workflows will be an asset. Experience with various supervised and unsupervised machine learning methodologies in areas common to the business such as anomaly detection, time series forecasting, clustering, event prediction, and other areas.
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Identify and build new client relationships with large municipal and Federal clients for Wastewater & Sanitary Sewer Evaluation Studies (SSES), NPDES Stormwater Services, Watershed Studies, and Water / Wastewater / Stormwater Design, Wet Infrastructure Management and Condition Assessment, Surface Water Quantity and Quality Monitoring and Analysis, Live Modeling / AI / Machine Learning Flood Prediction, Adaptive Control design and implementation, and HABs Prediction Machine Learning.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions with clients.
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Relevant areas of experience might include deep learning techniques, systems software, high performance computation, numerical algorithms, data science, cheminformatics, medicinal chemistry, structural biology, molecular physics, and/or quantum chemistry, but specific knowledge of any of these areas is less critical than intellectual curiosity, versatility, and a track record of achievement and innovation in the field of machine learning.
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MS or PhD in Computer Science, Computer Engineering or Electrical Engineering or related field in Deep Learning, Machine Learning, and Computer Vision or equivalent experience. Analyze, design, and implement optimized GPU algorithms for large-scale data analytics and machine learning.
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