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Independently perform sophisticated data analytics (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data.
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The candidate should have expertise in data modeling, SQL, Python, R, data warehousing, big data technologies, data pipeline construction, data quality, cleansing, version control, cloud services, machine learning, feature engineering, deep learning, and natural language processing.
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Full understanding and experience working with various technologies to include Python coding, JSON files, Zeek data, Cloud, Azure, AWS, and Artificial Intelligence/Machine Learning (AI/ML.
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A deep technical background in applied data science, spanning some or all statistics, experimentation, machine learning, causal methods, optimization techniques, data engineering and architecture (applied to large data), and behavioral analytics.
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Bachelors degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics, or related Quantitative disciplines and 5+ years experience in predictive analytics or equivalent field.
RemoteExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Strong programming experience with R and/or Python for statistical modeling and other machine learning applications. + Familiar with current and emerging techniques in analytics (machine learning, deep learning, AI.
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Proficiency in Python or R, with experience in machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). We are looking for someone who is passionate about data science, with a strong background in machine learning, statistical analysis, and team leadership.
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BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related fields and minimum 4 years related business experience in analytics, data science, predictive modeling, machine learning, statistical modeling and/or user experience role OR advanced degree and 2 years directly related experience.
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Experience in mathematics (statistics, linear algebra, differential calculus); data visualization (Tableau, Power BI, Qlikview); programming (SQL, Python, R, Java); data analysis (feature engineering, data wrangling, EDA) and machine learning (classification, regression, reinforcement learning, deep learning, clustering, dimensionality reduction.
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Bachelors degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related field and minimum 8 years of related experience, of which at least 4 years of directly related data analytics, data science, predictive modeling, machine learning, statistical modeling experience OR advanced in the required fields and 4 years directly related data science, analytics experience.
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Experience in Data Science and Machine Learning and interest in model development. Work closely with the data team to enhance and optimize ETL pipelines, ensuring data accuracy and availability for analytics and machine learning purposes.
Full-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Proven data science leveraging advanced statistical methods, Machine Learning/Artificial Intelligence, Natural Language Processing (NLP) modeling and model evaluation is a plus. Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Machine Learning, Project Management, Software Development, Stakeholder Relationship Management.
$101,100 - $159,100 a yearFull-timeExpandApply NowActive JobUpdated 29 days ago - UpvoteDownvoteShare Job
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This area has a unique appetite for a wide scope of model methodologies, from simple rules-based models to advanced machine learning and AI models which facilitates opportunities for both immediate, effective contribution on team priorities and personal development through exposure to advanced modeling techniques.
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The Anti-Money Laundering Modeling and Advanced Data Insights 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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The WW Installments team within Consumer Payments (CP) brings together the best of machine learning, econometrics, tech, business, and finance to deliver for customers across the world. 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.
$127,300 - $247,600 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago
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