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Candidates aiming to integrate modern methods of data science (DS), machine learning (ML) and artificial-intelligence (AI) to accelerate advances in their respective research areas are encouraged to apply.
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5+ years of experience in machine learning engineering, data science, or a related field. Knowledge of machine learning algorithms, statistical modeling, and data structures.
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Strong software development (preferably, Python) and experience working with libraries and packages related to data manipulation, statistical analysis, visualization, and machine learning algorithms and deep learning framework.
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Applies engineering principles and practices in design, development, analysis, and release of projects including but not limited to: Conveyor design (conventional flat belt & modular plastic belt) Auxiliary equipment design (discharge chutes, control stations, operator & machine platforms, etc.
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Net, C#, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Python, Data Modeling, SQL, SSIS, SSAS, SSRS, Power Automate, Power Platform, AI Builder, Power Apps, Blue Prism, Automation Anywhere, UiPath Studio, Orchestrator, ERP, QuickBooks, SAP, NetSuite, Oracle, API, JSON, XML, Web Services, SOAP, Postman, Fiddler, Integration, Custom Activities, DLL, Insight, Automation Hub, Task Capture.
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Coursework or work experience applying predictive modeling techniques from data science, statistics, machine learning, and econometrics to large data sets. Qualifying coursework may include—but is not limited to—data science, statistics, machine learning, optimization, numerical analysis, scientific programming, computational methods, supervised learning, unsupervised learning, text mining, and image analysis.
$118,000 - $178,000 a yearFull-timeExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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The Principal ML Research Scientist will also have a hands-on roll and is expected to customize and create various machine learning algorithms to operate over multi-domain data and optimizing the performance of those algorithms on the data.
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Experience in data integration and data governance practices, and familiarity with relevant data protection and privacy regulations. As Principal HR Data Analyst, this hands-on role will drive HR data discovery and collection, data security, data cataloging, data transformation, data analysis, data visualization, and reporting in support of the organization's overall HR Data & Reporting objectives.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. We are seeking Full Stack Software Engineers who are passionate about marrying data with emerging technologies.
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We integrate off-the-shelf and new development efforts to sustain and enhance Defense Intelligence Agency’s (DIA) National Media and Exploitation Center (NMEC) architecture by leveraging cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members.
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Strong knowledge of various database technologies (SQL, NoSQL), data integration (ETL/ELT) frameworks, data security (ZTA, ICAM, ACCM) and DoD cloud services (AWS, Azure, GCP). The Data Security Engineer is responsible for providing subject matter expertise to the Chief Data Officer (CDO) Directorate and to support senior level leadership within the Office of the Deputy Chief Information Officer, Special Access Program Information Technology (DCIO SAP–IT.
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The platform will be designed for District wide use and integration with other OCTO Enterprise Data tools such as Esri, Tableau, MicroStrategy, API Gateways, and Oracle databases and integration tools.
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The Director of Ontology and Data Modeling will be responsible for partnering with Technology, Machine Learning, and other Capital One teams to support the development and integration of semantic technology into Capital One products and services.
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CUDA (Compute Unified Device Architecture) /OpenCL (Open Computing Language) Programming: Develop and optimize applications using CUDA or OpenCL, harnessing the full potential of GPU hardware for parallel processing, high-performance computing, and machine learning on Linux platforms.
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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy.
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data administrator machine learning integration jobs in Bethesda, MD
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