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Expert level of understanding of NLP, NLU and Machine learning/Deep learning methods. Do applied research on a wide array of text analytics and machine learning projects, file patents and publish the papers.
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Knowledge of natural language processing, text analytics/mining, semantic technology, and/or machine learning. 4+ year of experience in ETL tools, data mining and data wrangling software (SSIS, SAS, Alteryx, Trifacta , or others.
$92,700 - $201,900 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Demonstrated depth in advanced analytics / data science technologies (e.g., machine learning, operations research, statistics, structural equation modeling, factor analysis, data mining, NLP techniques.
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Experience in Data Science, Data Mining, Machine Learning, Predictive Modeling best practices. Experience in Data Science, Data Mining, Machine Learning, Predictive Modeling best practices.
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The Executive Director, Insights Delivery will oversee a team that works closely with the Insurance Product Marketing teams and Creative and Channel Management functions. We are seeking a highly skilled and experienced Marketing Analytics executive Leader to join our marketing team as the Executive Director, Insights Delivery.
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This role is responsible for utilizing, developing and adapting analytical toolkits to derive actionable insights in support of growth marketing objectives for the Insurance business. Agility to collaborate and influence peers and business partners as organization matures across Enterprise Marketing Data & Analytics (e.g., marketing and ad tech.
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Use advanced knowledge in machine learning, statistics, text mining, natural language processing, computational semantics, computer vision, and data science to develop creative solutions to complex real-world problems.
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7+ years of practical/applied experience with machine learning methodologies and with data mining, statistical modeling, and/or equivalent. We are looking for a highly-skilled and experienced machine learning engineer to join the.
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Statistics, machine learning , data mining, data auditing, aggregation, reconciliation, and visualization. Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for various areas of the organization.
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Embed machine learning, artificial intelligence and GenAI capabilities into the cloud applications and solutions to enable predictive analytics, data mining, and pattern recognition for driving productivity and efficiency in solutions delivered.
$114,375 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
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You will drive both short term and long-term research initiatives in areas such as artificial intelligence, machine learning & data mining, natural language processing, bigdata systems, information and data visualization, social & cognitive science.
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Integrating innovative approaches in individual and team work products such as machine learning, artificial intelligence, data mining, predictive modeling, neural networks and simulation to mitigate price/value leakage across the pursuit and delivery phases of an engagement.
$181,800 - $350,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Apply data mining, NLP, and machine learning to real-world problems and datasets. Extensive hands-on expertise in machine learning (Supervised/Unsupervised, Causal, Bayesian, Reinforcement, or Deep Learning.
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