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Consult on using business intelligence data for predictive analytics and facilitating implementation of new tools, including Excel macros, SPSS, ArcGIS, or Access. Bachelor's degree in a Social Science field and 5+ years of experience in justice research and quantitative analysis, or Master's degree in a Social Science field and 3+ years of experience in justice research and quantitative analysis.
$123,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Experience with machine translation and transcription of foreign language documents using Microsoft Azure translation services. Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc.
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Baker Hughes Cordant Process Optimization solution is based on a novel approach that combines process domain knowledge along with advanced machine learning techniques. Minimum of 10 years of experience implementing Advanced Process Control (APC) and/or optimization solutions, including but not limited to DMCplus, DMC3, SMOC, PACE, RMPCT, Profit suite, ROMeo, or similar technologies within the process industry.
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Ideal candidate has knowledge in: Containerization, Cluster Administration, CI/CD Deployments, IAC’ed Bootstrap and Deployment ● Experience with Machine Learning Engineering (MLE); worked on deploying machine learning models and applications to Kubernete ● 6+ years working with AWS constructs, at least one major serverless application architecture/deployment.
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MS/PhD in areas of interest which include Defense (biosecurity, intel, threat assessment), Machine learning and modeling (computational biology, bio- or medically focused AI/ML, digital twins, predictive and multi-scale modeling) and chemistry (medicinal, organic, inorganic.
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This individual will work on exciting design projects and emerging-tech engagements—the latter focusing on things like identity intelligence, immersive technology, artificial intelligence/machine learning (AI/ML), virtualization, augmented reality and digital transformation.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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Superior modeling and analytical skills applying predictive modeling techniques from finance, statistics, mathematics, data science, and computer programming to large data sets. Experience with all phases of natural catastrophe modeling, including event / hazard generation, vulnerability measurement and financial impact analysis for pricing risks.
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Develop predictive (machine learning and deep learning) and prescriptive (mathematical optimization and simulation) analytic models in support of the organization’s clinical, operations and business initiatives and priorities.
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Hand held scanner, telephone, hand held radio, computer, printer, scanner, copier, fax machine, writing instrument, reports, logs, spreadsheets, merchandising diagrams (planograms), point-of-sale terminal, petroleum and/or propane equipment and terminals, fertilizer and crop protectant blenders and spreaders, loaders, forklifts, pick-ups, delivery trucks, and other tools and equipment.
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As part of a growing team this role will have the ability to leverage and work with new capabilities as they are deployed including deception infrastructure, continuous penetration testing, data loss prevention (DLP), and machine learning capabilities.
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The Python scripts will use supervised and unsupervised ML (both text and image-based machine learning), natural language processing (named entity extraction, summarization, etc.) Experience with machine learning, algorithm analysis, and data clustering.
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Validating and training AI machine learning models with annotated training sets in tuning accuracy of the AI models for CLM use cases;Demonstrating knowledge of machine learning and artificial intelligence workloads and considerations on Azure;Demonstrating knowledge of Azure Blob storage, Azure Service Bus and Azure Key Vault cryptography;Designing solutions for custom applications using the Microsoft.
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Experience with implementing machine learning pipelines using TensorFlow, Numpy, Scikit-Learn, OpenCV, DVC, W&B, TFLite, SNIPE, SHAP, UMAP, or ART. Process data and information at massive scale as an Artificial Intelligence (AI) and Machine Learning (ML) Engineer with machine learning technologies.
$220,000 a yearFull-timeExpandApply NowActive JobUpdated Today
machine predictive jobs Company: Techflow in Washington, DC
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