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Advanced degree, e.g., Ph. D. or M.S. in deep learning, neural networks, machine learning, data science, computer science, electrical engineering, engineering, statistics, engineering, industrial systems, mathematical sciences, applied mathematics, or Physics.
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Our Data Science Intern will be responsible for working on data science projects that drive strategic business objectives. Knowledgeable in Prescriptive Modeling like Machine Learning, Deep Learning, Recommendation, Search, or NLP.
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Expertise in at least one of the following domains: affective neuroscience, cognitive science, deep learning, and advanced analysis of fMRI data (e.g., encoding and decoding models.
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The position is open to applicants employing any methodology in their research and teaching, but applicants with specializations in computational approaches at the intersection of Science & Technology and International Affairs such as GIS, machine learning, deep learning, natural language processing, Bayesian statistics, network analysis, or other computational tools are especially encouraged to apply.
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Expertise in various data science methods and techniques, such as supervised and unsupervised learning, natural language processing, computer vision, deep learning, optimization, and simulation.
$170,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Experience in setting up supervised & unsupervised ML/NLP models including data cleaning, data analytics, feature creation, model section & ensemble methods, performance metrics & visualization.
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In the new era of AI, this role within Azure CXP Data & Applied Sciences team will provide you the opportunity to work on cutting-edge GenAI and ML (Machine Learning) solutions that drive specific, measurable, and impactful improvements to key areas of Azure customer experience.
$294,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Experience with data science tools and technologies (e.g., TensorFlow, PyTorch, scikit-learn) Stay current with industry trends and advancements in data science tools and technologies (e.g., TensorFlow, PyTorch, scikit-learn.
$321,550 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with LLMs and Deep learning models to develop business and data science solutions. 4+ years of related work experience in the field of Data Science & Machine learning.
$160,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Strong technical background with a deep understanding of data processing frameworks, machine learning algorithms, and AI technologies. You will work closely with cross-functional teams, including UX, engineering, data science, and consuming application teams to deliver the core analytics engine that will power all of Forge’s innovative solutions.
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Drive the adoption of cutting-edge technologies and methodologies in data engineering and AI, including machine learning (ML), data science, and advanced analytics. Deep expertise in cloud platforms, particularly Microsoft Azure, and familiarity with tools like Azure Data Factory, Azure Synapse, Fabric or other comparable and relevant technologies.
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As needed, collaborate with internal and external collaborators to identify optical character recognition, automation, predictive modeling, pattern analysis, natural language processing, fraud detection, and other business cases for using data science.
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Experience with full-stack engineering development for deep learning and LLM solutions. The desired candidate is an innovative, a hands-on coder with previous experience developing large-scale platforms utilizing data engineering, machine learning and cloud platforms & services.
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Candidate should know how to utilize Graphs Datasets (Neo4J or Knowledge graph Data sets) in “Data Science graphs use cases and Algorithms” (clustering, community detection, DFS, BFS, GNN and CNN and Deep Learning, etc.
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Proficiency in modern data science tools and frameworks, such as PyTorch, Tensorflow, JAX, Scikit-learn, and Keras. Proven experience (3-5 years) as a Data Scientist or Machine Learning Engineer, with experience in deploying Generative AI based solutions in production.
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