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Working knowledge appropriate analytic methods and methodological tools in one or more of the following areas: Applied mathematics ( e.g. probability and statistics, formal modeling, computational social sciences) Computer programming ( e.g. programming languages, math/statistics packages, computer science, machine learning, scientific computing) Visualization ( e.g. GIS/geospatial analysis, telemetry analysis.
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Design, develop and implement data science projects, including machine learning models, deep learning models, NLP solutions, statistical analysis, and data visualization.
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Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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Experience in Machine, and Deep Learning frameworks, model validation and deployment tools, data pipeline technologies, and visualization and data storytelling tools (R, Tableau, Jupyter, etc.
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Deep Learning and Computer vision. 2) Data Science/Machine learning track. Difference between Machine learning, Artificial Intelligence and Deep learning.
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5+ years of experience across a breadth of data science, AI and machine learning disciplines including, but not limited to: forecasting, natural language processing (topic modeling, semantic search, text classification), deep learning and GPU-based algorithms (CNN, LSTM), computer vision.
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Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
$200ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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In this client-facing role, you will support business leaders in the successful development of data strategies, data governance programs, data modernization roadmaps, reporting and visualization tools, and craft business cases for funding of data initiatives at large corporations, in particular regard to EHS and ESG functions.
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Data science, machine learning, optimization models, Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)Doctorate, Masters: Artificial Intelligence.
$117,000 - $234,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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In this role, you will support the successful development of data strategies, data governance programs, data modernization roadmaps, reporting and visualization tools, and craft business cases for funding of data initiatives at large corporations, in particular regard to EHS and ESG functions.
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Experience with data engineering and data science concepts (data modeling, data cleansing, data visualization, machine learning, deep learning, natural language processing, computer vision, etc.
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We combine expertise across multiple fields: high-performance scientific computing, physics-based modeling and simulation, data science, machine learning, applied mathematics, optimization, statistics, decision support, data analysis and visualization, computer systems architecture, quantum computing, neuromorphic computing, human-technology connections, and others.
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Proficiency in survey methodology, statistical analysis, and data visualization techniques, with expertise in software tools such as SPSS, SAS, R, or STATA. 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.
$160,000 - $284,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Recent or soon-to-be completed Ph. D. (typically completed within 3 years) in Computer Science or Mathematics with strong background in one or more of the following: Statistical machine learning, Bayesian deep learning, probabilistic and differentiable programming, probability and measure theory.
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Through this opportunity, you will work with a multi-disciplinary team consisting of engineers, scientists, and clinicians to process large biomedical datasets, develop and evaluate machine learning algorithms, and implement data visualization tools for advanced medical imaging technologies.
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5 Common Interview Mistakes
Everyone's interview process is unique in some form or fashion. Like most, your interview process is crafted so you can get the most information out of your candidates to increase hiring confidence and make the right hiring decisions. However, there are often small problems in interview processes that could ultimately affect the success of hiring decisions.
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When tax time rolls around, the last thing you want to worry about is having to track down a W-2 from your former employer. Many times you won’t have to because the IRS requires companies to send these forms to all current and former employees who have earned more than $600 in the last year. Unfortunately, there are employers who don’t do what they’re supposed to. There are even times where something else may happen that prevents the W-2 from getting where it’s supposed to go.
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