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Machine Learning: Artificial Neural Network (ANN), GANs, Bayesian Network/BBN, Regression, Logistic Regression, Decisions Tree, Elastic-net regularized generalized linear models (built in R), k-NN, SVM, Clustering, Page Rank and PCA, MCA, MFC, aPriori and other Data Mining and Deep Learning Algorithms.
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Data Science, Decision Analytics, Data Mining, Information Sciences, Information Technology, Quantitative Analysis, Operations Research, Operations Analytics, MBAs with Analytical Focus, Engineering, Computer Science, Statistics, Data Management, Decision Science, Quantitative Science, Mathematics, Information Systems, Industrial Engineering, Artificial Intelligence, Computer Vision, Machine Learning, Natural Language Processing.
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Researches and identifies Artificial Intelligence (AI) methods – including Machine Learning (ML) and Natural Language Processing (NLP) methods. The Data Scientist will be responsible for managing, understanding and analyzing in-house and customer data – including text mining, developing predictive systems, risk scoring, creating efficient algorithms, data quality improvement and other related activities.
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Your Role and Responsibilities As a Senior Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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One (1) year of working experience in Machine Learning, Deep Learning, or Artificial Intelligence. Contributes to the development of machine learning (ML) and Artificial Intelligence (AI) models from development through testing and validation.
$99,400 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Researches and implements cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence to make data analysis more efficient. Specialization in Machine Learning (ML) or Artificial Intelligence (AI) preferred.
Full-timeExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Proficiency in common geospatial software applications and tools, such as visual programming (JEMA, FADE/MIST, ECO/ETAS), Python, SQL, Git, GIMS, A WS Sagemaker, A WS Cloud, ESRI ArcGIS, statistics (descriptive, Bayesian), Markov-Chain modelling, TensorFlow, Linear Algebra, R, SAS, NLP.
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Are you fascinated by the possibilities presented by the IoT, machine learning, and artificial intelligence advances? Experience with machine learning, data mining, statistics, or graph algorithms in academic or internship environments.
$137,000 a yearFull-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Data mining, advanced statistical analysis (e.g., statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations, artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g., model selection, evaluation, and sensitivity analysis), experience as a data scientist working to support a single or multiple domain area, and/or software engineering.
$185,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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QineitQ is looking for a results-driven Data Scientist to support NSG strategies through the creation of automated collection, models, dynamic analytic models, workflow automations, and any other automation processes and products as assigned.
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Comfortable with both relational databases and Hadoop-based data mining frameworks, SQL, Snowflake, and ML/AI tools on the Hyperscalers (AWS, Azure, GCP) Expertise in analyzing large, complex, multi-dimensional datasets using a variety of tools like Python, R, Statistical Analysis System (SAS), or Statistical Package for the Social Sciences (SPSS.
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Deep understanding of statistical and predictive modeling concepts, machine learning approaches, clustering and classification techniques, and recommendation and optimization algorithms. One (1) year of working programming experience in Python, Ruby, R, Matlab, Scala, or Java.
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Position Overview QineitQ is looking for a results-driven Data Scientist to support NSG strategies through the creation of automated collection, models, dynamic analytic models, workflow automations, and any other automation processes and products as assigned.
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Must have relevant experience in two or more of the following: designing/implementing machine learning, data mining, advanced analytical algorithms, programming, data science, advanced statistical analysis, artificial intelligence, or software engineering.
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