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Statistics Tableau and Power BI PL/SQL and databases both SQL and NoSQL Data structures and algorithms Artificial Intelligence and Machine learning Machine learning Algorithms Decision Tree and Random Forest Algorithms Naïve Bayes and KNN Algorithm Support Vector Machine (SVM) Statistics Random variables, Zscore, Hypothesis testing, Expected Value Predictive Modeling : Different kind of Business problems and different phases of Predictive modeling and Popular Modeling Algorithms.
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And experience applying it to real-world projectsStrong knowledge in the application of Machine LearningExperience with common data science toolkits, such as SQL, R and/or Python with high proficiency in the use of opensource statistical and machine learning packages (numpy, pandas, scikit-learn, stats tool etc.
ExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Experience with data analysis tools and platforms such as SQL, Hadoop, Spark, or similar. Strong knowledge of AI technologies, including machine learning, natural language processing, and computer vision.
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Proficiency in data analysis tools such as SQL, Python, R, or similar. They will have strong SQL experience, understand how data relates to business, and be comfortable communicating with internal and external clients.
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Candidates can be based in Charlotte, NC, or any of the client's other offices in the listed cities: Charlotte, NC, East Hartford, CT, Dallas, TX, Plano, TX, Providence, RI, Stamford, CT, or Wilmington, DE. Our client is looking for a Data Engineer with Intermediate to advanced knowledge of SQL, SAS, Alteryx, Python, Tableau, or related tools.
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The Senior Data Engineer role will be responsible for developing and implement a range of analytics and automation solutions, including data extraction, analysis, reporting, and dashboard design, but could include more advanced analytics including statistical analysis, text mining & NLP, and modeling / machine learning / AI.
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Advanced data analytics - designing and building solutions using technologies such as Azure Data Factory, Azure Data Lake, HD Insights, SQL DWH, Stream Analytics, Machine Learning, R Server, Synapse, Azure Machine Learning (AML), Azure Kubernetes Service (AKS) for model deployments, Vector and Retrieval-Augmented Generation (RAG) implementation.
$120 an hourFull-timeExpandApply NowActive JobUpdated 12 days ago - UpvoteDownvoteShare Job
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Advanced proficiency in data analysis tools and programming languages such as Python,R (optional), and SQL and/or Apache Spark for data analysis and machine learning applications.
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Expertise in statistical programming, data mining and machine learning tools (Python, SAS, R, etc.) Minimum7 years of experience with SAS or SQL, or other data management, reporting and query tools (SharePoint, SAP, Business Objects, Tableau, Crystal reports/Dashboard, etc.
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Programming languages used for statistical analysis and data programming including SAS, R, C. Stochastic Modeling, Optimization, Simulation, Computational Statistics, and Machine Learning.
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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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Experience with model development, machine learning/artificial intelligence, and data science. Utilize analytical skills to independently develop analytics & automated testing solutions using tools like Alteryx, Tableau, SQL, SAS, and Python.
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As a Senior Associate in our Risk Analytics and Modeling team, you’ll have the opportunity to apply your quantitative, modeling and analytical skills in a real world environment to develop or validate statistical, financial engineering, and AI/machine learning models in the areas of credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics area.
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Experience with one or more of the following a plus: Model Development, Machine Learning / Artificial Intelligence, and Data Science. Intermediate to advanced knowledge of one or more of the following: SQL, SAS, Alteryx, Python, Tableau or related tools.
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Solid understanding of data analysis techniques, machine learning algorithms, and statistical methodologies. Experience with data visualization tools such as Tableau, Power BI, or matplotlib.
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