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11 West 19th Street (22008), United States of America, New York, New YorkManager, Data Science - Fraud, Deep LearningManager, Data Scientist, Fraud. The Fraud Data Science team builds the machine learning models that help protect our customers and Capital One against fraudsters.
$229,900 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Opportunity: Machine learning experts on our team can utilize applied science and software development skills to help tweak Foundation Models that help us address some of the hardest problems towards our vision in making insights from complex Industrial data simple & easy to access.
Full-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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At least 2 years’ experience with Pytorch, Tensorflow or other Deep Learning frameworks. At least 2 years’ experience building advanced Deep Learning architectures (for example: RNN’s, CNN’s, Transformers.
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As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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The Card Fraud Data Science team builds the machine learning models that help protect our customers and Capital One against fraudsters. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
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They offer deep technical knowledge in areas like machine learning, statistical modeling, data analysis, and big data processing. Director of Data ScienceLocation: Tysons Corner, VAClearance: US CitizenIntegral Federal is hiring a Director of Data Science to support program evaluations, conducts opportunity technical analysis, and identifies and aligns initiatives to broader business goals and objectives.
ExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Build and deploy scalable data science algorithms by applying statistical analytics, Machine Learning (ML), Anomaly detection, and other techniques to enable supply planning. Machine Learning - knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests, Deep Learning and an understanding of how to use pre-trained models for different cases.
Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Strong proficiency in statistical analysis and modeling techniques, such as linear regression, logistic regression, decision trees, random forests, clustering, deep learning algorithms, boosting, text mining and NLP.
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2+ years' experience working with Deep Learning frameworks (Keras, TensorFlow, PyTorch). 8+ years' experience in and solid knowledge of analytics and data mining techniques including the following: 5+ years' applied data science implementation experience in a business setting.
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S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for hands-on entry-level ML scientists and NLP/Gen AI/ LLM scientists to grow into the next step in their career journey and apply her or his technical expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while conducting cutting-edge applied research around LLMs, Gen AI, and related areas.
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Publications or experience in machine learning, AI, computer vision, optimization, computer science, statistics, applied mathematics, or data science. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, and applied mathematics.
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8+ years of expertise in various AI/ML techniques, such as deep learning, natural language processing, computer vision, recommender systems, reinforcement learning, large language models, etc.
RemoteExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Experience with deep learning framework and infrastructure like TensorFlow or PyTorch. Develop data science solutions based on tools and cloud computing infrastructure. Bachelors degree in computer science, mathematics, physics, statistics, or related field.
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Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R, and Python) along with applied mathematics, ML, and Deep Learning frameworks (such as TensorFlow) and ML techniques (such as random forest and neural networks.
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Familiar with deep learning platforms (e.g., Keras, Tensorflow) and related classification and segmentation algorithms. Proficient at machine learning algorithms, familiar with algorithms like Generalized Linear Model, Random Forest, CART, and/or deep learning.
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