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In this role, you will be part of a team working in a fast-paced, open-ended environment with cutting edge technologies in deep learning and generative AI. You’ll help define and influence how our firm’s data scientists and business teams leverage data and machine learning to improve our processes and products.
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Hybrid, 3 daysExperience with machine learning tools such as scikit-learn, R, Theano, TensorFlow, SparkML, or FoundryExperience in using two or more of the following modeling types to solve business problems: classification, regression, time series, clustering, text analytics, survival, association, optimization, reinforcement learning.
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Providing hands-on leadership for projects pertaining to statistical modeling and machine learning approaches to effectively challenge and influence the strategic direction and tactical approaches of these projects.
$125,000 - $210,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Additionally, it would be great if they have knowledge of:Version ControlPython Machine Learning and Modeling (scikit-learn, etc.) Need to be well versed with Python, SQL, and PowerBI.
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Knowledge of statistical modeling and machine learning concepts and techniques including: regression, feature selection, random forest, etc. Manage and optimize processes for data intake, validation, mining and engineering as well as modeling, visualization and communication deliverables.
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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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Center 2 (19050), United States of America, McLean, VirginiaLead Machine Learning Engineer, Finance TechAs a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning (ML) applications and systems at scale.
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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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Collaborate with Analysts, Business Intelligence Engineers and Product Managers to implement algorithms that exploit rich data sets for statistical analysis, and machine learning. Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL, AWS – Redshift, and OLAP technologies, Model data and metadata for ad hoc and pre-built reporting.
Full-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
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Bachelor's Degree or higher in one of the following fields: computer science, mathematics, physics, statistics, or another computational field with a strong background of using machine learning/data mining for predictive modeling or time series analysis.
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Machine Learning Infrastructure: Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and experience in designing and implementing machine learning infrastructure.
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We are looking for strong engineers who have a background in generative AI and NLP, with experience in areas like language model evaluation; data processing for pre-training and fine-tuning; responsible LLMs; LLM alignment; reinforcement learning for language model tuning; efficient training and inference; and/or multilingual and multimodal modeling.
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De monstrates proficiency in most areas of mathematical analysis methods, machine learning, statistical analyses, and predictive modeling and in-depth specialization in some areas.
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Team is on a journey to modernize the way Capital One identifies potential money laundering, terrorist financing, and human trafficking through the use of machine learning, statistics, and other advanced analytic techniques.
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