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Considerable knowledge of various machine learning algorithms and their applications, including Random Forest, GBM, XGBoost, deep learning, NLP, computer vision, multi-modality. - Proficiency in Python, and experience with deep learning frameworks such as PyTorch, Tensorflow/Keras, MXNet.
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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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Experience in R, Python or similar applicable programming languages, with some experience utilizing Artificial Intelligence (AI) and Machine Learning (ML) tools and techniques.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Master's Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science.
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Expertise in open source data science technologies such as Python, R, Spark, SQL. Strong understanding of machine learning algorithms, techniques, and frameworks, including deep learning, neural networks, and ensemble methods.
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Superior computer skills are required, with knowledge in relevant software packages and languages such as, but not limited to, SAS, R, Python, SQL, Java, and. ● Theoretical fluency and working proficiency in the application of a broad array of statistical and quantitative methods such as description and inferential statistics, multivariate regression, clustering, neural networks, predictive modeling, forecasting, machine learning, data mining, and optimization algorithms.
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Expert proficiency in SQL, encompassing standard knowledge for Google BigQuery and Snowflake, along with proficiency in scripting languages (Python, R). In-depth comprehension of data science concepts and tools, encompassing machine learning algorithms, statistical analysis, and proficiency in data visualization libraries.
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Experience developing and applying statistical or machine learning methods in a corporate environment through applications such as R, python, SAS, SPSS, S, S-PLUS, or Stata.
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Advanced degree in a quantitative discipline, strong programming skills (R, SQL, Python), expertise in machine learning and statistical modeling, experience with cloud deployment and services, familiarity with airline revenue management algorithms.
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Minimum of 4+ years of experience using data manipulation tools such as SAS, SQL, R, or Python, Business Objects, or other tools to query large databases and manipulate large data files.
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Apply machine learning, data mining, and visualization techniques to make accurate and actionable analyses in a timely fashion. Responsible for using statistical methodology to ensure that testing, learning and production goals are met.
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Experience in advanced analytics tools (Python, R) along with applied mathematics, ML, Deep Learning frameworks (such as TensorFlow), and ML techniques (such as random forest and neural networks.
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The ideal candidate is adept at using big data sets and applying machine learning and artificial intelligence techniques for analysis and prediction tools focused on environmental and meteorological applications.
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Strong expertise in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and statistical modeling techniques. Proficient in programming languages such as Python, R, and SQL for data manipulation and analysis.
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If you thrive in a dynamic environment, enjoy pushing the boundaries of what's possible with AI and machine learning, and want to be part of a mission-driven organization, we would love to hear from you.
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