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Continue to develop and help drive the strategy for the organization's data strategy including data architecture, Reporting, Insights, Analytics, Operations, Predictive modeling, attribution and Machine Learning/AI.
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Working closely with the CFO, the Senior Business Intelligence Analyst uses advanced techniques that integrate traditional and non-traditional datasets to enable analytical solutions, and successfully applies predictive analytics, machine learning, simulation, and optimization techniques to generate management insights and enable customer-facing applications.
$90,000 - $120,000 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Strong knowledge of statistical analysis, predictive modeling, machine learning, and optimization techniques. Develop and implement algorithms for data analysis and modeling. Proficiency in programming languages such as Python, R, or SQL, and experience working with big data platforms and tools (e.g., Hadoop, Spark.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Advanced experience in pattern recognition and predictive modeling. Develop & implement predictive models, algorithms, and machine learning solutions to identify patterns, trends, and potential risks in data.
Full-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Experience in pattern recognition and predictive modeling. Typically requires hands-on related experience in advanced analytics, big data, data visualization in Looker, PowerBI or Tableau, SQL/Python coding of relational databases, as well as project management experience.
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Interprets structured and unstructured data as well as other agency data and exercise independent judgment to produce statistical analytic products using regression time series, confidence intervals, predictive modeling, and exploratory data analysis.
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Master’s degree (or tis equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 5 years of relevant experience; or Bachelor’s degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 6 years of relevant experience.
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Experience with governance, controls, process and procedures, conceptual data modeling, master data management, data standardization and stewardship, information integrity and compliance, and data quality management.
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We design, develop, and deploy software solutions that collect, reconcile, and transform data for business intelligence, predictive analytics, and decision support. In this role you will work across our client engagements, providing expertise in data collection, data analysis, data mapping, data profiling, data mining, and data modeling.
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You will be responsible for inspecting, cleansing, transforming, and modeling data and will address issues related to data completeness and quality, as well as contribute to and produce technical and data process documentation.
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From our earliest days, we pioneered the use of predictive modeling to individually personalize credit card offers, turning the entire industry on its head. Part of a team driving the bank’s omni-channel servicing portfolio responsible for setting and delivering an experience framework on how our customers should be serviced in both digital and digital-human interactionsLearning constantly.
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Position Description: CGI has an immediate need for a Sr. Quantitative/Modeling Analyst - Model Validation to join our financial services team. Predictive Analytics - Knowledge of, experience with and ability to use the tools, processes and practices for predicting business trends and providing forecasts that drive business decisions and business planning.
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Experience in data mining, descriptive analytics, application of statistical methods, analyses and modeling, predictive modeling, opportunity assessment and quantification, and simulation.
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High proficiency in statistical analysis, predictive modeling, machine learning algorithms, and data mining techniques. Apply advanced statistical analysis and predictive modeling techniques to analyze datasets.
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Proficiency in data analysis techniques and tools, such as statistical analysis, data visualization, and predictive modeling. Monitor and report on HR analytics trends, emerging technologies, and innovative practices to enhance HR data capabilities.
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