Matt currently is a global lead instructor for General Assembly's Data Science Immersive program in ten cities across the U.S and most enjoys bridging the gap between theoretical statistics and real-world insights. Matt is a recovering politico, having worked as a data scientist for a political consulting firm through the 2016 election. Prior to his work in politics, he earned his Master’s degree in statistics from The Ohio State University. Matt is passionate about putting the revolutionary power of machine learning into the hands of as many people as possible. When he isn’t teaching, he’s thinking about how to be a better teacher, falling asleep to Netflix, and/or cuddling with his pug.

<description>&lt;p&gt;Matt currently is a global lead instructor for General Assembly's Data Science Immersive program in ten cities across the U.S and most enjoys bridging the gap between theoretical statistics and real-world insights. Matt is a recovering politico, having worked as a data scientist for a political consulting firm through the 2016 election. Prior to his work in politics, he earned his Master’s degree in statistics from The Ohio State University. Matt is passionate about putting the revolutionary power of machine learning into the hands of as many people as possible. When he isn’t teaching, he’s thinking about how to be a better teacher, falling asleep to Netflix, and/or cuddling with his pug.&lt;/p&gt;</description>

Matt currently is a global lead instructor for General Assembly's Data Science Immersive program in ten cities across the U.S and most enjoys bridging the gap between theoretical statistics and real-world insights. Matt is a recovering politico,

Matt currently is a global lead instructor for General Assembly's Data Science Immersive program in ten cities across the U.S and most enjoys bridging the gap between theoretical statistics and real-world insights. Matt is a recovering politico, having worked as a data scientist for a political consulting firm through the 2016 election. Prior to his work in politics, he earned his Master’s degree in statistics from The Ohio State University. Matt is passionate about putting the revolutionary power of machine learning into the hands of as many people as possible. When he isn’t teaching, he’s thinking about how to be a better teacher, falling asleep to Netflix, and/or cuddling with his pug.

Global Lead Developer for Data Science at General Assembly

A couple months ago Andres Meneses and I sat down at a busy Adams Morgan cafe in the heart of Washington, DC to discuss his success as a frontend developer. Incredible to his story is how he navigated from a successful long-term position at The World Bank to a coding boot camp to gain a foothold in the web development world. His background is one of the many success stories popping up from mid-career individuals making a jump into the world of data science/technology development.

<description>&lt;p&gt;A couple months ago Andres Meneses and I sat down at a busy Adams Morgan cafe in the heart of Washington, DC to discuss his success as a frontend developer. Incredible to his story is how he navigated from a successful long-term position at The World Bank to a coding boot camp to gain a foothold in the web development world. His background is one of the many success stories popping up from mid-career individuals making a jump into the world of data science/technology development.&lt;/p&gt;</description>

A couple months ago Andres Meneses and I sat down at a busy Adams Morgan cafe in the heart of Washington, DC to discuss his success as a frontend developer. Incredible to his story is how he navigated from a successful long-term position at The World B...

A couple months ago Andres Meneses and I sat down at a busy Adams Morgan cafe in the heart of Washington, DC to discuss his success as a frontend developer. Incredible to his story is how he navigated from a successful long-term position at The World Bank to a coding boot camp to gain a foothold in the web development world. His background is one of the many success stories popping up from mid-career individuals making a jump into the world of data science/technology development.

World Bank to Front End Developer

One of the world's top data science boot camps, General Assembly, offers world-class instruction from leading data science instructors. In this three-part series, we interview the staff who train, enable and get nascent data scientists employed.

<description>&lt;p&gt;One of the world's top data science boot camps, General Assembly, offers world-class instruction from leading data science instructors. In this three-part series, we interview the staff who train, enable and get nascent data scientists employed.&lt;/p&gt;</description>

One of the world's top data science boot camps, General Assembly, offers world-class instruction from leading data science instructors. In this three-part series, we interview the staff who train, enable and get nascent data scientists employed.

Teaching Data Science with Dr. Farshad Nasiri 

Ben Miller is an Associate Economist at the RAND Corporation and a Professor at the Pardee RAND Graduate School. His research spans a wide variety of topics including disaster mitigation, infrastructure finance, energy resilience, geospatial information, insurance, tax policy, regulatory affairs, healthcare supply, agriculture, econometrics, and beyond.  Recent publications examine the link between flood insurance prices and housing affordability, review federal policies surrounding transportation and water infrastructure finance, estimate the causal impact of weather warning systems on fatalities and injuries from tornadoes, and overview econometric techniques for determining the value of geospatial information. Prior to joining RAND, Miller worked as a statistician supporting the U.S. Census Bureau’s Survey of Income and Program Participation. He holds a Ph.D. in economics from the University of California, San Diego and a B.S. in economics from Purdue University.

<description>&lt;p&gt;Ben Miller is an Associate Economist at the RAND Corporation and a Professor at the Pardee RAND Graduate School. His research spans a wide variety of topics including disaster mitigation, infrastructure finance, energy resilience, geospatial information, insurance, tax policy, regulatory affairs, healthcare supply, agriculture, econometrics, and beyond.  Recent publications examine the link between flood insurance prices and housing affordability, review federal policies surrounding transportation and water infrastructure finance, estimate the causal impact of weather warning systems on fatalities and injuries from tornadoes, and overview econometric techniques for determining the value of geospatial information. Prior to joining RAND, Miller worked as a statistician supporting the U.S. Census Bureau’s Survey of Income and Program Participation. He holds a Ph.D. in economics from the University of California, San Diego and a B.S. in economics from Purdue University.&lt;/p&gt;</description>

Ben Miller is an Associate Economist at the RAND Corporation and a Professor at the Pardee RAND Graduate School. His research spans a wide variety of topics including disaster mitigation, infrastructure finance, energy resilience, geospatial information,

Ben Miller is an Associate Economist at the RAND Corporation and a Professor at the Pardee RAND Graduate School. His research spans a wide variety of topics including disaster mitigation, infrastructure finance, energy resilience, geospatial information, insurance, tax policy, regulatory affairs, healthcare supply, agriculture, econometrics, and beyond.  Recent publications examine the link between flood insurance prices and housing affordability, review federal policies surrounding transportation and water infrastructure finance, estimate the causal impact of weather warning systems on fatalities and injuries from tornadoes, and overview econometric techniques for determining the value of geospatial information. Prior to joining RAND, Miller worked as a statistician supporting the U.S. Census Bureau’s Survey of Income and Program Participation. He holds a Ph.D. in economics from the University of California, San Diego and a B.S. in economics from Purdue University.

Data Science at RAND

Dr. Paul J. Nicholas is an operations research scientist at the Johns Hopkins University Applied Physics Laboratory (JHU APL). He also teaches a graduate course on analytics and decision analysis as part of GMU’s Data Analytics Engineering (DAEN) program and serves in the U.S. Marine Corps Reserve. Paul’s research focuses on the use of advanced analytic techniques to examine problems in national security, including large-scale combinatorial optimization, simulation, and data analytics. Paul received his B.S. from the U.S. Naval Academy, his M.S. from the Naval Postgraduate School, and his Ph.D. from George Mason University. On active duty, he deployed several times to Iraq and Afghanistan in support of combat operations as a communications officer and operations research analyst. He was a visiting fellow to the Johns Hopkins University Applied Physics Lab, and an MIT Seminar XXI Fellow. He is the author of numerous peer-reviewed publications and holds two U.S. patents.

<description>&lt;p&gt;Dr. Paul J. Nicholas is an operations research scientist at the Johns Hopkins University Applied Physics Laboratory (JHU APL). He also teaches a graduate course on analytics and decision analysis as part of GMU’s Data Analytics Engineering (DAEN) program and serves in the U.S. Marine Corps Reserve. Paul’s research focuses on the use of advanced analytic techniques to examine problems in national security, including large-scale combinatorial optimization, simulation, and data analytics. Paul received his B.S. from the U.S. Naval Academy, his M.S. from the Naval Postgraduate School, and his Ph.D. from George Mason University. On active duty, he deployed several times to Iraq and Afghanistan in support of combat operations as a communications officer and operations research analyst. He was a visiting fellow to the Johns Hopkins University Applied Physics Lab, and an MIT Seminar XXI Fellow. He is the author of numerous peer-reviewed publications and holds two U.S. patents.&lt;/p&gt;</description>

Dr. Paul J. Nicholas is an operations research scientist at the Johns Hopkins University Applied Physics Laboratory (JHU APL). He also teaches a graduate course on analytics and decision analysis as part of GMU’s Data Analytics Engineering (DAEN) pro...

Dr. Paul J. Nicholas is an operations research scientist at the Johns Hopkins University Applied Physics Laboratory (JHU APL). He also teaches a graduate course on analytics and decision analysis as part of GMU’s Data Analytics Engineering (DAEN) program and serves in the U.S. Marine Corps Reserve. Paul’s research focuses on the use of advanced analytic techniques to examine problems in national security, including large-scale combinatorial optimization, simulation, and data analytics. Paul received his B.S. from the U.S. Naval Academy, his M.S. from the Naval Postgraduate School, and his Ph.D. from George Mason University. On active duty, he deployed several times to Iraq and Afghanistan in support of combat operations as a communications officer and operations research analyst. He was a visiting fellow to the Johns Hopkins University Applied Physics Lab, and an MIT Seminar XXI Fellow. He is the author of numerous peer-reviewed publications and holds two U.S. patents.

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