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Proving specialization background in data science, including experience with statistical analysis, data mining, predictive modeling, and machine learning; Demonstrating a thorough level of knowledge in statistical modeling, algorithms, data mining, and machine learning algorithms problem solving.
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Specialized experience for this position must include: Experience with data science and analytical methods from conducting machine learning, Natural Language Processing, and technical procedures such as, solution design, implementation, and deployment.
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Develop innovative solutions that leverage machine learning, artificial intelligence, and cloud technologies to transform data handling and analytics. Proven Expertise: 12+ years of experience in data architecture, with a solid understanding of data modeling, ETL processes, and modern data frameworks (e.g., DataBricks, Snowflake, Azure.
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Center 1 (19052), United States of America, McLean, VirginiaLead Machine Learning Engineer (Python, Analytics)As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.
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Utilizes leading software, emerging technologies, such as automation and machine learning, and theoretical models to conduct in-depth simulation to identify, assess, mitigate supply chain risks and evaluate supply chain scenarios.
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Experience with, and/or strong understanding of programming languages, machine learning, and statistics. Experience with statistical research techniques, including modeling, data mining, clustering, and segmentation.
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Success in the role requires an innovative mind, a proven track record of delivering next generation software and data products, rigorous analytical skills, and a passion for delivering customer value through automation, machine learning and predictive analytics.
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Position also requires two (2) years of experience in each of the following: Agile methodologies or SAFe Software Development Principles; Designing data models and solutions for analytical and reporting use cases; Machine learning, statistical analysis, and predictive modeling; Python, R, and SQL; Hadoop, Hive, MySQL, and NoSQL; Tableau and Power BI; and Software development lifecycle.
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Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Machine Learning, Project Management, Software Development, Stakeholder Relationship Management.
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Leveraging machine learning techniques and statistical programming packages to perform analysis on commodity instruments. We assist our clients with analytical support in complex commodity risk topics such as hedging, trading and procurement optimization, market risk management, reporting tools and complex contract modeling, including energy, agriculture, metals, and soft commodities.
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Skilled in artificial intelligence and machine learning (e.g., SageMaker) Experience with Machine Learning or Artificial Intelligence. Arcfield was purpose-built to defend against the near-peer threat through innovations in systems engineering and integration, modeling, simulation and analysis, space and launch support, cybersecurity and test range support.
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Typical Licensure Preferred qualifications: Experience in machine learning and generation of force-fields and modeling of catalysts and energy materials will be an added advantage.
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These include cyberspace operations, electronic warfare, intelligence, data analysis and fusion, tactical network design, wireless communications, radar, sensors, electro-optics, mission command applications, autonomy and machine learning, power and energy, modeling and simulation, counter-IED, minefield detection/defeat and assured positioning, navigation and timing.
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Invent, implement and deploy state-of-the-art machine learning models, algorithms and systems as part of the OCI Speech team. Is very experienced with Machine Learning and Deep Learning models and frameworks.
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Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Direct experience in multi-physics modeling and optimization with applications in wearable actuation and sensing research.
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modeling machine learning jobs in Richmond, VA
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