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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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This role combines the expertise of a data scientist with the responsibility of overseeing and optimizing our Enterprise Resource Planning (ERP) system in strong coordination with the Group IT. The ideal candidate will have a strong background in data science, statistical analysis, and machine learning, coupled with hands-on experience in managing business processes (Offer to Cash -OTC) within the ERP systems.
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Machine Learning and Deep Learning (Some or all): Deep neural networks(CNN, RNN, LSTM), Supervised methods such as Tree based models (random forest, xgboost, Light GBM), K-NN, SVM as well as Unsupervised methods such as Clustering (Hierarchical, K-mean, K-medoids), Dimensionality reduction (PCA.
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Looking for hands-on data scientist and strong Python coding skill is critical, much higher priority than NLP, IoT or Deep Learning. The newly hired Data Scientist will be a key interface with stakeholders in all Marketing functions, Business Technology, Sales and Sales Operations, and our shared machine learning teams throughout the organization.
Full-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Deploy and optimize machine learning solutions on massive datasets using big data technologies. Understands the core concepts of Machine Learning and the Math's behind it, good knowledge of existing Client tools and technologies.
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As an Associate Data Scientist, you will play a key role in expanding our influence by building and implementing machine learning models and supporting their field execution. Complete analytics (e.g., machine learning, artificial intelligence, advanced statistics) to support patient journey analysis and related analyses of interactions within the healthcare ecosystem.
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The US Card Data Science team builds industry leading machine learning models to empower core underwriting decisions in the acquisitions and management of new and existing credit card customers.
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The Team: S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for an experienced ML scientist and hands-on NLP/Gen AI/ LLM senior scientist to grow into the next step in their career journey and apply her or his domain expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while mentoring and growing a ML Data Science team.
$180,000 - $225,000 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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At AML, we develop cutting-edge machine learning solutions that enable current and future products and services for the enterprise! Hands-on experience with building Deep Learning applications.
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Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation. At least 3 years experience with machine learning.
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Leverage NGS and machine learning techniques together with the sequencing and data science teams to improve the development of tailored AAV capsids. Excellent hands-on skills in cell and molecular biology techniques and assay development are required.
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Hands-on experience with Autonomous Systems, Big Data Analytics, AI, Machine Learning (ML), Data Visualization, and advanced statistical techniques is highly desired. Have experience with statistics, machine learning algorithms, or general algorithm development.
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Hands-on experience with deep learning libraries (TensorFlow, PyTorch, etc.) Experience with anomaly detection and synthetic data strategies for machine learningExperience with computer vision (CNN, Transformer architectures) and image/video data preparation for machine learningHands-on experience with time series analysis and sequence modelingExperience with Cloud environments (Azure, AWS-SageMaker, S3, etc.
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3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience. Hands-on experience in developing models, in optimizing model training and tuning and in deploying LLMs such as GPT, LLaMA, Falcon, BERT, or Transformer-based architectures.
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Strong hands-on experience in the Python toolkit for imaging data manipulation, feature extraction and machine learning (e.g., numpy, scikit-learn, pytorch, etc. The ideal candidate will have strong hands-on experience in applied machine learning for healthcare, especially in medical imaging analysis.
$113,000 - $195,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago
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