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Expertise in Python, R, SQL, statistics, data mining. Visualize insights using Microsoft Office, Tableau, Python, R. In this role, you will conduct sophisticated data analytics, data mining, exploratory analysis, predictive analysis, and statistical analysis.
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SQL, R, Python, Hadoop, SAS, SPSS, Scala, AWS. Statistics, machine learning , data mining, data auditing, aggregation, reconciliation, and visualization. Navy Federal Credit Union assesses market data to establish salary ranges that enable us to remain competitive.
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Proficient in programming languages such as Python, R, SQL, Java, or Scala and in debugging and diagnosing. Expertise with data visualization tools such as Spotfire, Tableau, RShinyApp or Python Dash.
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Demonstrated depth in advanced analytics / data science technologies (e.g., machine learning, operations research, statistics, structural equation modeling, factor analysis, data mining, NLP techniques.
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Experience in Cost Data Analysis and Predictive Analytics; Tableau & Alteryx’ Experience with data mining/analytics programming languages such as Python, R, SQL, or BA.
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Experience in data access tools, such as SAS, SQL, Python, and R. Experience in statistical detection of potential fraud, waste, abuse, and improper payments in healthcare using tools such as predictive modeling, development of mathematical models, neural networks, and data mining and other analytical methods.
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Prior experience with R, SAS or SPSS, other data mining tools, databases, and computer programming. 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.
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5+ years' experience working with statistical analysis, object-oriented programming, data mining / model building, business intelligence, visualization methodologies and tools such as R, Python, SAS, Looker, Tableau, Hue and TOAD Experience and working knowledge of data and analytics in a healthcare data management environment.
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Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
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Proficient in common geospatial software applications and tools, such as visual programming (JEMA, FADE/MIST, ECO/ETAS), Python, SQL, Git, GIMS, AWS Sagemaker, AWS Cloud, ESRI ArcGIS, statistics (descriptive, Bayesian), Markov-Chain modeling, TensorFlow, Linear Algebra, R, SAS, NLP.
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Knowledge of data mining and analytic methods such as Clustering / Cluster Analysis, Factor Analysis, Regression Models, Logistic Regression, Predictive Modeling, optimization models, etc.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Languages: R, Python (Pandas, Seaborn, Scikit-learn), SQL,Hive, Pig, Impala, Sqoop, Kafka, VBA, Shell.
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Advanced Analytics - Applied Econometrics, Advanced Calculus, Statistical Methods, Data Visualization, Decision Analytics & Optimization, ML, Big Data, Social Network Analytics. Techniques: Statistical Analysis, Visualization, Optimization, Machine Learning, Big Data, Data Warehouse, NLP.
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Perform statistical analysis and data mining to create predictive systems. Significant experience as a Data Scientist or advanced analytical role. Design, develop, and test ML applications using Python, Linux, Docker.
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