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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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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
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Industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in their technical domain area (e.g., NLP, CV, etc.
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Sustainability Science and Innovation (SSI) is a multi-disciplinary team within WW Sustainability combining science, analytics, economics, statistics, machine learning, product development, and engineering expertise.
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Intermediate Expertise in engineering Azure Automation Azure Machine Configuration (Guest Configuration), OMS, State Configuration (Azure DSC), Update Management, Runbooks, Inventory Management, Change Tracking.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly detection. Experience with DevSecOps, CI/CD, IaC and CaC, IT Infrastructure Library, and IT Service Management.
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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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You will function as part of a world class Data Science team to support various AI and machine learning initiatives Solve complex marketing and business challenges by accessing, integrating, manipulating, mining, and modeling a variety of data sources Reframe client business questions into data science deliverables.
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Experience with AI, machine learning, blockchain, IoT, or other emerging technologies. Possess one at least ONE of the following certifications, OR, be able to obtain prior to start date: CASP+ CE; CCISO; CCNA Cyber Ops; CCNSecurity; CCNP Security; CEH; CFR; CISA; CISM; CISSP (or Associate); CISSP-ISSAP; CISSP-ISSEP; Cloud+; CySA+ ; GCED; GCIA; GCIH; GICSP; GSLC; SCYBER.
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Understands, conducts, and documents appropriately Dialysis/Apheresis machine safety tests/alarm tests, equipment calibration, dialysate testing, machine safety tests, functional testing, and internal and external disinfection on all water & dialysis machines, and complies with the documentation/notification standards per FMS policies.
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Machine Learning Frameworks: Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. + AI/ML Application: Apply machine learning and artificial intelligence techniques to enhance data processing and analytics capabilities.
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Cleans and disinfects dialysis machine surface, chair, equipment, and surrounding areas between treatments according to inpatient renal services policies and procedures. Performs all required pre-treatment dialysis machine alarm testing.
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Are you a machine learning (ML) engineer or data scientist with development skills who relishes the opportunity to leverage and deploy AI models within a solution? Knowledge of Databricks, PyTorch, Tensorflow, and Langchain.
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We are seeking an engineer with a technical background in one of the following disciplines: systems engineering, applied operations research, modeling and simulation, RF and satellite communications, artificial intelligence and machine learning (AI/ML), or applied data analytics.
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LMI is seeking a seasoned Lead Data Scientist to spearhead the development, testing, and deployment of machine learning (ML) models. Deep knowledge and practical experience with delivering sophisticated data analysis and machine learning solutions using Python.
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machine job Title: marketing Company: Adobe in Arlington, VA
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