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The AI COE is seeking a Senior Data Scientist with experience in Conversational AI, Generative Large Language Models, Natural Language Processing, Machine learning, various deep learning related technologies, predictive and prescriptive analytics.
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Develop experimental and analytic plans for machine learning algorithms and data modeling processes, use of strong baselines, and ability to accurately determine cause and effect relations.
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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 have 2-5 years of successful technical experience in the domain of predictive analytics (e.g. data science, machine learning, data mining, and statistics related work); preferably in the Oil & Gas industry.
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Data science, machine learning, optimization models, PhD 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.
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AI and Machine Learning: Utilize state-of-the-art AI and machine learning techniques, including natural language processing (NLP), to train the chatbot for accurate and effective communication.
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As a Data Scientist at Netomi, you will drive NLP and machine learning projects and be responsible for developing methodology and solutions to support technical, analytical, and operational requirements.
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Minimum of 7 years of experience in ML development and deploying ML solutions in cloud-based production environments for a Senior MLS IMinimum of 9-12 years of experience in ML development and deploying ML solutions in cloud-based production environments for a Senior MLS IIMachine learning: Strong mathematical foundation and understanding of the concepts underlying classic machine learning, deep learning, NLP, statistical modeling, and data analysis.
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Grainger Applied Machine Learning spans across Recommender Systems, Generative AI, Optimization and Simulation, NLP, and other Machine Learning / Deep Learning-based applications.
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To join our team in Washington, DC. In this role you will work across our client engagements, providing expertise in machine learning algorithms, natural language processing (NLP), data collection, data analysis, data mapping, data profiling, data mining, data modeling, and data visualization.
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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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This high performing team works with clients to implement the full spectrum of data analytics and data science, from data architecture and storage to data engineering and querying, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as robotic process automation (RPA.
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Machine learning: Strong mathematical foundation and understanding of the concepts underlying classic machine learning, deep learning, NLP, statistical modeling, and data analysis.
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As a Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals. You will implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Build and maintain strategic partnerships with technology vendors and professional services firms specializing in advanced analytics, generative AI, Natural Language Processing (NLP), machine learning and advanced data management technologies.
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