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The Payment Model Implementation Analytics Consultant will provide support on a number of payment model implementation contracts requiring intermediate SAS, R, Python, or SQL experience as well as knowledge of statistics and research methodology.
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Experience with data analytics/visualization tools and communicating analysis (SQL, Google BigQuery, Tableau, programming language (R, Python, or SAS. The individual must possess strong communication and data mining skills, and be familiar with the programming tools, statistical software and technology used by the CPE team (e.g., SQL, Tableau, R, Python.
$85,000 - $95,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Proficiency in programming languages such as Python, R, or Java. Expertise in machine learning, statistical modeling, data visualization, and familiarity with big data technologies and cloud platforms including AWS, Azure, or Google Cloud.
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Experience with one or more general purpose programming languages including but not limited to: Python, R, Scala, Spark. 3+ years of work/educational experience in Artificial Intelligence/Machine Learning.
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Experience in providing business solutions which require analytic tools such as R, Python, AWS, and Databricks to build advanced analytic models, and exposure to accessing data from cloud platforms and big data systems.
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6+ years of experience in Programming R, Python ML space. Job Description: Metas Solutions has an opening for an experienced Senior Data Scientist/Machine Learning Engineer to work Remotely.
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Programming in Python, R, and SQL. Proficiency in machine learning techniques such as dimensionality reduction, resampling, ensemble learning, anomaly detection, feature scaling and feature selection.
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Strong proficiency in data analysis, machine learning, and statistical modeling techniques, with experience using tools such as Python, R, SQL, and/or TensorFlow. Strategy Development : Develop and execute a comprehensive data science strategy aligned with business goals and objectives, leveraging advanced analytics, machine learning, and AI technologies.
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Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark. Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (e.g., AWS, Google Data Analytics, Microsoft Azure.
$119,025 - $198,375 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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With minimal guidance, write, document, and deploy custom code in a variety of environments (Python, SAS, R, etc.) In supporting rule analysis, Teammate should be able to Independently perform sophisticated data analytics that fit to the fraud problem being observed (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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Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). The ideal candidate will have a strong background in artificial intelligence, machine learning, and data analytics.
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Two or more of the following other languages: Python, SQL, Java, C#, R, JavaScript, Go, Spark. The Machine Learning practice designs and delivers innovative Machine Learning solutions as part of intelligent products on Amazon Web Services, Azure and Google Cloud using core cloud data science tools, MLOps components, and other big data related technologies.
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Proficiency in programming languages such as Python, R, or SQL, with experience in libraries/frameworks such as TensorFlow, PyTorch, Scikit-learn, Langchain, etc. You understand the data science lifecycle and are experienced in development and implementation of advanced statistical models and machine learning algorithms.
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Technical leadership experience and programming skills using SPSS, SAS, Python or R. Hands on programming skills using SPSS, SAS, Python or R. Hands on experience on Machine Learning, Artificial Intelligence, and/or Big Data.
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Data Scientist is an expert in at least 1 programming language (e.g. R, SAS, Python), has proficiency in statistical theory and underlying mathematical distributions, and expertise in querying relational databases with SQL.
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