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Must have a strong background in one or more of the following: Mathematical, Statistics, Probability, Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
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What Additional Experience Makes A Strong Candidate: 4+ years of production experience with Scala 4+ years of production experience with Micro Services / Streaming Services Experience addressing ML problems, particularly in domains such as Time Series, Computer Vision (CV), Natural Language Processing (NLP), and data mining Proficiency with popular ML frameworks (Xgboost, TensorFlow, PyTorch, etc.
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Exceptional programming skills in Python, with popular deep learning and natural language processing (NLP) tools and libraries, including Scikit-learn, Pandas, PyTorch, TensorFlow, or other leading deep learning frameworks, NLTK and spaCy for natural language processing tasks.
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Familiarity with and knowledge of machine learning, natural language processing, text analytics, web data collection, and advanced data visualization is a plus.
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Create cyber threat intelligence conclusions by using data science and analysis (e.g. outlier detection, gap analysis, normalization, machine learning, automated models, natural language processing, etc.
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Experience with statistical methodologies and machine learning techniques such as: neural networks, graphical models, ensemble methods, forecasting, linear programming, natural language processing, LLMs.
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Preferred Skills 5+ years in a data engineering role with demonstrable experience with Cognitive computing, data integration, data mining, Natural Language Processing, Hadoop platforms, and automating machine learning components.
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This may also include patent work related to image processing, databases, access management, natural language processing/understanding (NLP/NLU), and autonomous machines/vehicles.
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Our specialized data centers run computing-intensive applications powered by clean energy for: Cryptocurrency Mining Artificial Intelligence Deep Learning Machine Learning Scientific Computing Natural Language Processing Video Transcoding and more.
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They also use and advise on such tools as machine learning, natural language processing, web scraping, big data platforms, and data visualization techniques and their application to relevant public policy issues.
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As a member of our Machine Learning Research team, you will design new approaches to derive insights from Pfizer's proprietary data and external datasets to generate testable hypotheses across the drug discovery continuum with a focus on extracting biological knowledge.
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Experience as a Machine Learning engineer building feature engineering pipelines, deploying AI models, and optimizing model inference. Design and develop machine learning and deep learning systems using appropriate ML algorithms/frameworks.
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Responsibilities: Developing and training machine learning models using Natural Language Processing (NLP) techniques. Requirements: Advanced degree (Ph. D. preferred) in a field like Applied Linguistics, Computational Linguistics, or Data Science, with a focus on building and deploying machine learning models for text analysis.
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Having experience with productizing machine learning models within a cloud service (e.g., AWS, Azure, GCP) and data science environments (e.g., Databricks) is a plus. You also have opportunities to research and develop applications in applied artificial intelligence using computer vision, natural language processing (NLP) and large language models (LLM.
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Experience in data analysis, statistical learning, and machine learning. Experience with multiple deep learning techniques such as Transformers, CNN, LSTM, RNN, etc., in addition to standard machine learning approaches such as those found in scikit-learn.
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machine learning natural language processing big data jobs Title: data scientist Company: Cardinal Health
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