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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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We are looking for a Senior Data Scientist to help drive actionable insights using artificial intelligence and machine learning algorithms. 9+ years of relevant experience conducting text mining, NLP, machine learning, deep learning, artificial intelligence techniques-based models.
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Relevant experience must be in one or more of the following (for Entry level) but in two or more for Full Performance, Senior, and Expert levels: designing/implementing machine learning, data mining, advanced analytical algorithms, programming, data science, advanced statistical analysis, artificial intelligence, computational science, software engineering, or data engineering.
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Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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CUDA, Bash, and/or SQL), machine learning / deep learning methods, data analytics, and medical image analysis. Preferred Experience: Experience with common open-source scientific computing/machine learning libraries (e.g., PyTorch / TensorFlow), containerization, and cloud-native technologies (Docker & Kubernetes) is preferred.
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Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc.
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The Workplace Investing Data Engineering and Exchange AI Delivery Chapter team is looking for a Senior Machine Learning Engineer to join our team to help deliver customer facing AI models into production.
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Applies a variety of methods based on standards and metrics to review and improve data acquisition and data management processes such as statistical analysis, machine learning, data mining, predictive analytics, time series analysis, multivariate regression analysis, statistical process control and optimization solutions.
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Statistical Background : Proficiency in statistics and machine learning techniques, particularly when applied to meteorological data. Data Visualization : Effective data visualization skills for time series and geospatial data.
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Three (3) years of enterprise experience as a data scientist, informaticist, statistician, senior analyst, or related role. Collaborates with the Data Linkage Scientist and other team members to improve Master Person Index (MPI), Master Provider Registry (MPR), and other link index match rates.
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Microservices and App services, Cloud Managed SQL, Big data/data lakes, AI and Machine Learning, Azure Blobs, Office 365. AI and Machine Learning, Azure Blobs, Office 365, Dynamic 365, Logic apps, Power apps, MS Flow, Power BI, Sharepoint o GitHub DevOps, CI/CD, workflows, actions and Ansible automations Skills Required : o Cloud solutions, design, architecture and security o Evaluating hardware.
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Category II certification as a vibration analyst in industrial plant setting utilizing portable vibration data collector/analyzer and associated diagnostic and reporting software. Perform rotating machinery fault diagnosis, troubleshooting, and condition evaluation utilizing diagnostic skills to interpret frequency spectrum and time based waveform data.
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Experience in statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch). 5 years of experience in AI applications (e.g., Deep Learning, NLP, Computer Vision, or Pattern Recognition.
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Description: As a Data Engineer, you'll be responsible for designing, building, and maintaining data pipelines and infrastructure to support data analytics, machine learning, and business intelligence initiatives.
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E.g. Alteryx, PowerBi, Tableau, Snaplogic and RPA technologies (UiPath, Automation Anywhere, PowerAutomate, etc), and machine learning/Artificial Intelligence. Demonstrate knowledge of technologies that support collaboration, automation and data-driven story-telling including: Microsoft Products (Teams, PowerBI, MS Office), G-Suite (Google), and business intelligence tools.
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