Amanda P Email & Phone Number | Accomplished data analyst with management experience. In depth knowledge of data mining, mathematical modeling, forecasting, machine learning, and strong software skills including proficiency in SAS, Python, R, and SQL. Possesses the ability to solve complex problems with quantitative methods while adopting new software, languages, and platforms rapidly. Articulate communicator who has demonstrated: team leadership abilities, technical and analytical proficiency. Technology Skills: R, R Markdown, Python, SQL, SAS, and MS Office Data Science Skills: Statistical modeling, predictive modeling, data mining, dimensionality reduction techniques, data analysis, data visualization

Amanda P

Accomplished data analyst with management experience. In depth knowledge of data mining, mathematica...
Austin, Texas Metropolitan Area, United States

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Amanda P’s Email amanda.p@schwab.com

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Amanda P’s Location Austin, Texas Metropolitan Area, United States

Amanda P’s Current Industry Charles Schwab

Amanda P’s Prior Industry Texas Neurorehab Center | Lakeway Regional Medical Center | Us Army

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Work Experience

Charles Schwab

Senior Manager, Analytics Consultant

2020-06-01 00:00:00 - Present

Texas Neurorehab Center

Clinical Dietitian

2014-10-01 00:00:00 - 2016-12-01 00:00:00

Lakeway Regional Medical Center

Clinical Dietitian

2014-12-01 00:00:00 - 2016-07-01 00:00:00

Us Army

Combat Medic

2004-09-01 00:00:00 - 2010-07-01 00:00:00

Skills

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Languages

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FAQ About Amanda P

Amanda P is located at
Austin, Texas Metropolitan Area, United States

Amanda P is a Accomplished data analyst with management experience. In depth knowledge of data mining, mathematical modeling, forecasting, machine learning, and strong software skills including proficiency in SAS, Python, R, and SQL. Possesses the ability to solve complex problems with quantitative methods while adopting new software, languages, and platforms rapidly. Articulate communicator who has demonstrated: team leadership abilities, technical and analytical proficiency. Technology Skills: R, R Markdown, Python, SQL, SAS, and MS Office Data Science Skills: Statistical modeling, predictive modeling, data mining, dimensionality reduction techniques, data analysis, data visualization