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Ideal candidates have a strong publication record in areas including artificial intelligence data mining, machine learning, natural language processing, and/or fields such as cognitive science, learning analytics, and psychometrics.
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We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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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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We are looking for a passionate, talented, and resourceful Senior Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have a strong machine learning background and a desire to push the envelope in one or more of the above areas.
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Good understanding of machine learning, deep learning (including LLMs) and natural language processing and ability to optimize machine learning models to adapt to solving various kinds of issues.
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Experience with natural language processing (NLP) and deep learning frameworks TensorFlow, PyTorch). Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI.
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As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Expertise in a subset of the following: machine learning, object detection, image segmentation, computer vision, image processing, remote sensing, spectral science, neural models for autonomous vehicles/robotics, structure from motion (SfM), natural language processing (NLP), large language models, data fusion, change detection, and pattern of life analysis.
$229,000 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations.
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Experience in natural language processing (NLP) and integrating chatbot agents into existing systems would be beneficial and is considered a plus. While not mandatory, we highly value candidates with expertise in machine learning (ML) and experience in developing custom chatbot agents.
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Helps team advance on plans for use of artificial intelligence, including Natural Language Processing, ChatGPT, predictive analytics, and leveraging machine learning to find hidden insights in data.
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Stay abreast of the latest advancements in machine learning, natural language processing, and quantitative finance, and apply cutting-edge techniques to enhance the Trexquant’s investment capabilities.
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Minimum of ten years of experience with pattern recognition, machine learning, linguistics, utterance classification, and signal processing knowledge. Minimum of five years of experience with Natural Language data collection analysis and tagging, grammar analysis, NLU development, and directed dialog grammar development.
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Proficiency in Python, with strong skills in relevant data science and machine learning libraries such as TensorFlow, PyTorch, scikit-learn, and pandas. Apply sophisticated machine learning methods, including deep learning, optimisation, and causal analysis, to develop innovative models for biological data analysis.
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machine learning natural processing jobs Title: data analyst Company: Delphi Technologies
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