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As a Data Scientist in the Garage, youll be part of a team thats leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across large number of customer records to harness the power of AI in unlocking the big opportunities to improve customer experience.
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Demonstrated ability to work with large data sets using Python and SQL for data mining and machine learning. Knowledge of data science and machine learning methods and models (clustering, classification algorithms, neural networks, etc.
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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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Support National Security clients as a Data Scientist performing data science, analytics, data wrangling, statistical analysis, and machine learning. This high performing team works with clients to implement the full spectrum of data analytics and data science, from data architecture and storage to data engineering and querying, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as robotic process automation (RPA.
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Utilizes an in-depth knowledge of data science techniques and methodologies such as machine learning, predictive analysis, prescriptive analysis and optimization, and other emerging analytical techniques to assist, consult, or lead others in the application of data science techniques.
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Deploy sophisticated analytics programs, machine learning and statistical methods. Proficiency with common ML models such as Deep Learning, Logistic Regression, Decision Tree, Random Forest, XGBoost, FacebookProphet.
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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.
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Familiar with current and emerging techniques in analytics (machine learning, deep learning, AI) + Strong programming experience with R and/or Python for statistical modeling and other machine learning applications.
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Experience with data modeling, machine learning algorithms, optimization, and data science techniques e.g. decision trees, SVM, neural networks, time series, forecasting, classification, regression, clustering, cross-validation, and model evaluation.
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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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6-9 years of experience with predictive modeling, databases, computational simulation, clustering, machine learning, and remote computing in academia or industry. Model and build Machine Learning, Statistical algorithms on top of our vast number of datasets.
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Computational modeling of whole brain circuits, machine learning. Experts are here to help: Lab manager, Data scientist, MRI physicist, Wet lab assistant. Experts are here to help: Lab manager, Data scientist, MRI physicist, Wet lab assistant.
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Master’s degree or PhD in Engineering, Statistics, Machine Learning, Computer Science, Econometrics, or other quantitative fields. 7+ years of professional experience in Data Science, Machine Learning and Credit Risk or Fraud Strategies.
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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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