49 min
How to Simplify Weather Impact on Society with Jared Goldberg of WeatherOptics HumAIn Podcast - Artificial Intelligence, Data Science, Developer Tools, and Technical Education
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- Technology
[Audio]
Podcast: Play in new window | Download
Subscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSS
Jared Goldberg is the Head of Data Science at WeatherOptics. He owns a Bachelor of Science in Biopsychology, Cognition, and Neuroscience; Applied Statistics from University of Michigan.
Episode Links:
Jared Goldberg’s LinkedIn: https://www.linkedin.com/in/jared-goldberg-427462103
Jared Goldberg’s Twitter: @weatheroptics
Jared Goldberg’s Website:https://www.weatheroptics.co/ https://github.com/jaredbgo
Podcast Details:
Podcast website: https://www.humainpodcast.com
Apple Podcasts: https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009
Spotify: https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS
RSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9
YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag
YouTube Clips: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videos
Support and Social Media:
– Check out the sponsors above, it’s the best way to support this podcast
– Support on Patreon: https://www.patreon.com/humain/creators
– Twitter: https://twitter.com/dyakobovitch
– Instagram: https://www.instagram.com/humainpodcast/
– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/
– Facebook: https://www.facebook.com/HumainPodcast/
– HumAIn Website Articles: https://www.humainpodcast.com/blog/
Outline:
Here’s the timestamps for the episode:
(00:00) – Introduction
(01:36) – WeatherOptics started as a weather blog way back when, from our founder and CEO, Scott Pecoriello, he was a weather nut growing up. And he had this blog, it was on Facebook and social media. And his snowfall accuracies were crazy good. In November of 2017, he reached out to me to bring the business into this tech side of things and into the data side of things. And we have just been gaining momentum since then.
(03:15) – Quantitative forecasting was started in the 1920s by the Norwegians. The modern era of forecasting started in the 1980s and that's where we had global forecasting models based on a more complex system of observations, but still building off these physics concepts that were used originally. Since the 1980s things have just gotten more complex. These models have gotten better. And now there's this whole wild system that no one really realizes is happening where you have all of these different inputs from all these weather gauges, like airplanes and satellites, and they're all amalgamated and interpolated into these models.
(09:52) – To some extent, everyone has this inherent understanding that the weather changes our behavior. However, we need to keep in mind that our business and where we really understand the weather better is the short term weather events. It is these sorts of impacts that obviously are not as flashy as something like a hurricane or a tornado, but we feel understanding how weather impacts daily life at these smaller scales and these less major events actually can save people and companies a lot of money and can really improve their processes.
(14:11) – While some industries have been excluded or cut off, and obviously a lot of people are losing jobs, there are other industries that we are leaning on much heavier. And one of these industries is logistics. And one major application of our weather data is building useful ways to understand, not just that it is going to rain or I guess in this case, it is not just going to snow in. It's how is that going to affect your route? We are aware that weather has an impact on sales. So we consider weather data, a viable source of alternative data in terms of quantitative investing and things like that. We think these weather signals can help explain variations in other datasets that help us understand the market.
(17:46) –We have a combination of meteorological expertise, as well as ma
[Audio]
Podcast: Play in new window | Download
Subscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSS
Jared Goldberg is the Head of Data Science at WeatherOptics. He owns a Bachelor of Science in Biopsychology, Cognition, and Neuroscience; Applied Statistics from University of Michigan.
Episode Links:
Jared Goldberg’s LinkedIn: https://www.linkedin.com/in/jared-goldberg-427462103
Jared Goldberg’s Twitter: @weatheroptics
Jared Goldberg’s Website:https://www.weatheroptics.co/ https://github.com/jaredbgo
Podcast Details:
Podcast website: https://www.humainpodcast.com
Apple Podcasts: https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009
Spotify: https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS
RSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9
YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag
YouTube Clips: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videos
Support and Social Media:
– Check out the sponsors above, it’s the best way to support this podcast
– Support on Patreon: https://www.patreon.com/humain/creators
– Twitter: https://twitter.com/dyakobovitch
– Instagram: https://www.instagram.com/humainpodcast/
– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/
– Facebook: https://www.facebook.com/HumainPodcast/
– HumAIn Website Articles: https://www.humainpodcast.com/blog/
Outline:
Here’s the timestamps for the episode:
(00:00) – Introduction
(01:36) – WeatherOptics started as a weather blog way back when, from our founder and CEO, Scott Pecoriello, he was a weather nut growing up. And he had this blog, it was on Facebook and social media. And his snowfall accuracies were crazy good. In November of 2017, he reached out to me to bring the business into this tech side of things and into the data side of things. And we have just been gaining momentum since then.
(03:15) – Quantitative forecasting was started in the 1920s by the Norwegians. The modern era of forecasting started in the 1980s and that's where we had global forecasting models based on a more complex system of observations, but still building off these physics concepts that were used originally. Since the 1980s things have just gotten more complex. These models have gotten better. And now there's this whole wild system that no one really realizes is happening where you have all of these different inputs from all these weather gauges, like airplanes and satellites, and they're all amalgamated and interpolated into these models.
(09:52) – To some extent, everyone has this inherent understanding that the weather changes our behavior. However, we need to keep in mind that our business and where we really understand the weather better is the short term weather events. It is these sorts of impacts that obviously are not as flashy as something like a hurricane or a tornado, but we feel understanding how weather impacts daily life at these smaller scales and these less major events actually can save people and companies a lot of money and can really improve their processes.
(14:11) – While some industries have been excluded or cut off, and obviously a lot of people are losing jobs, there are other industries that we are leaning on much heavier. And one of these industries is logistics. And one major application of our weather data is building useful ways to understand, not just that it is going to rain or I guess in this case, it is not just going to snow in. It's how is that going to affect your route? We are aware that weather has an impact on sales. So we consider weather data, a viable source of alternative data in terms of quantitative investing and things like that. We think these weather signals can help explain variations in other datasets that help us understand the market.
(17:46) –We have a combination of meteorological expertise, as well as ma
49 min