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Familiarity with Natural Language Processing, Machine Learning, Predictive modeling, Statistical Analysis and Hypothesis testing. Is familiar with disciplines such as Natural Language Processing, Machine Learning, Predictive modeling, Statistical Analysis and Hypothesis testing.
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Experience and solid understanding of Natural Language Processing (NLP) methods and techniques. Familiarity with Natural Language Processing (NLP) methods and techniques.
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Design, develop and implement various process improvement tools and techniques including Workflow, Robotic Process Automation (RPA), Optical Character Recognition (OCR), Natural Language Processing and (NLP), Machine Learning (ML) to meet end-to-end business requirements.
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Design, develop and Deploy innovative Machine Learning, Natural Language Processing (NLP), Gen AI, and Graph Neural Network (GNN) models using Python/GCP or other modeling tools.
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Working knowledge of advanced techniques such as: SMOTE, dimension reduction techniques, natural language processing, sentiment analysis, anomaly detection, geospatial analytics, etc.
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Proficiency in data analysis tools (Python, R), machine learning frameworks (TensorFlow, PyTorch), and data visualization tools (Tableau, Power BI). Use natural language processing (NLP) and computer vision for unstructured data analysis in healthcare records and medical imaging.
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Minimum Experience: 2 years of process engineering experience in a chemical or petrochemical environment; with at least 2 years of experience using timeseries tools such as SEEQ, natural language processing (NLP), building predictive maintenance machine learning productions and taking them to production, building machine learning solutions with cloud tools (AWS, Azure, Google cloud), and knowledge of applying overall equipment effectiveness (OEE) calculations.
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If selected, you will be responsible for research, development, deployment, and enhancement of enterprise-wide analytics solutions using complex analytics techniques such as machine learning, natural language processing, robotics process automation, and artificial intelligence.
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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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Developing machine learning, data mining, statistical network, natural language processing, text analytics, and graph-based algorithms to analyze massive data sets. Unstructured text and natural language processing.
$76,224.72 - $113,633.52 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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2+ years of experience working with artificial intelligence (AI) techniques such as any of the following: machine learning, deep learning, and natural language processing, applying these techniques to solve complex business problems.
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Knowledge or experience in advance excel/MS Power BI/Tableau/QlikView. Knowledge or experience in VBA/SQL/HTML/JavaScript/automation software/workflow software/ RPA software (e.g. BluePrism, UiPath, Kapow, Automation anywhere, or others) would be an advantage.
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Advance data analytics offerings through proof-of-concept demonstrations including techniques such as Machine Learning, Artificial Intelligence, Predictive Analytics and Natural Language Processing.
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Experienced in implementing some machine learning techniques (may include supervised and unsupervised learning, deep learning, natural language processing, ensemble methods, dimensionality reduction.
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Possess a solid understanding of AI technologies, including machine learning, natural language processing (NLP), and computer vision, to facilitate the development and integration of advanced internal tools that enhance analytical capabilities and operational efficiency.
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