Mathematical Statistician (Data Scientist) - Direct Hire
Internal Revenue ServiceWHAT IS DATA AND ANALYTICS? A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions Position(s) are to be filled in the following area(s): DAO- Data and Analytics Office (DAO)-RESEARCH, APPLIED ANALYTICS & STATISTICS (RAAS) Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
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The following are the duties of this position at the full working level. If this vacancy includes more than one grade and you are selected at a lower grade level, you will have the opportunity to learn to perform these duties and receive training to help you grow in this position. Develops and evaluates statistical models, sampling methodologies, forecasting techniques, classification algorithms, and other quantitative approaches to identify trends, assess program performance, measure outcomes, and support evidence-based decision making. Identifies data sources, assesses data quality, and performs data preparation and integration. Conducts research studies, exploratory analyses, hypothesis testing, model validation, sensitivity analyses, and other statistical investigations to produce defensible and actionable findings. Develops innovative approaches for integrating and analyzing data from multiple internal and external sources to address emerging program needs. Reviews research proposals and provides recommendations to management. Prepares technical reports, briefing materials, presentations, and documentation describing methodologies, assumptions, findings, limitations, and recommendations. Defines study objectives, develops project methodologies, establishes analyticalrequirements, and determines appropriate statistical techniques to achieve project goals. Ensures analytical products are technically sound, reproducible, and aligned with organizational objectives. Serves as a technical consultant and advisor to managers, analyst, program officials and project teams on statistical methodologies, research design, data science applications, quantitative analysis, and interpretation of results.
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