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Brent Schneeman Phones & Addresses

  • 1903 Barton Pkwy, Austin, TX 78704 (512) 447-3579
  • 5660 Wagon Train Rd, Austin, TX 78749 (512) 288-3579
  • 1250 Capital Of Texas Hwy, Austin, TX 78746
  • West Lake Hills, TX
  • Phoenix, AZ
  • Mesa, AZ
  • Travis, TX

Resumes

Resumes

Brent Schneeman Photo 1

Vice President Data Science And Analytics

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Location:
Austin, TX
Industry:
Information Technology And Services
Work:
Overhaul
Vice President Data Science and Analytics

Alegion Dec 2017 - Apr 2020
Senior Director of Engineering

Dosh Jan 29, 2018 - Feb 2019
Senior Director, Data Science

Thought and Memory Jan 29, 2018 - Feb 2019
Managing Director

Homeaway.com Sep 2016 - Dec 2017
Senior Director, Data Science
Education:
Santa Fe Institute 2015 - 2015
University of Southern California 1988 - 1990
Bachelors, Bachelor of Science, Electrical Engineering
Carroll College 1985 - 1988
Bachelors, Bachelor of Arts, Mathematics, Physics
Big Sky High School
Pullman High School
Arizona State University
Skills:
Agile Methodologies
Software Development
Scrum
Java
E Commerce
Enterprise Software
Management
Scalability
Rest
Web Applications
Web Services
Payment Industry
Software Engineering
Leadership
Jsp
R
Integration
Strategic Planning
Jdbc
Servlets
Sql
Javase
Rough Diamonds
Tubing
Camping
Testing
Projects
Interests:
Economic Empowerment
Civil Rights and Social Action
Politics
Poverty Alleviation
Data Visualization
Making Photographs
Certifications:
Computing For Data Analysis
The Data Scientist’s Toolbox
R Programming
Kaggle R Tutorial on Machine Learing
Neural Networks and Deep Learning
License 1A988B8F631B31E182F4A3Db5A8Aa2...
Coursera
Datacamp, License 1A988B8F631B31E182F4A3Db5A8Aa2...
Brent Schneeman Photo 2

Brent Schneeman

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Publications

Us Patents

System, Apparatus And Method For Segregating Data In Transactions Via Dedicated Interface Elements For Isolated Logic And Repositories

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US Patent:
20130159169, Jun 20, 2013
Filed:
Dec 16, 2011
Appl. No.:
13/329182
Inventors:
Brent T. Schneeman - Austin TX, US
Dennis Kashkin - Austin TX, US
Eric M. Carr - Austin TX, US
Mark R. Reynolds - Austin TX, US
Matthew W. Kinman - Austin TX, US
Douglas A. Squires - Austin TX, US
Daniel A. Herrera - Fremont CA, US
Assignee:
HomeAway.com, Inc. - Austin TX
International Classification:
G06F 3/048
G06Q 20/08
US Classification:
705 39, 715780
Abstract:
Embodiments relate generally to computer software and computing devices, and more particularly, to a system, an apparatus and a method configured to segregate data at an interface of a computing device to facilitate on-line electronic payment transactions. In one embodiment, a method includes presenting fields configured to accept a first type of data and to accept a second type of data for an on-line electronic payment transaction. The method includes generating an initialization signal for transmission to an isolated data management system to initialize a portion of a memory associated with first type of data, responsive to an interaction with a field, receiving data from the field, and generating a save signal to save the data from the field in a portion of the memory. This can be responsive to a second interaction with the field.

Event Detection Using Inquiries

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US Patent:
20210083997, Mar 18, 2021
Filed:
Sep 28, 2020
Appl. No.:
17/035425
Inventors:
- Austin TX, US
Brent T. Schneeman - Austin TX, US
International Classification:
H04L 12/58
G06Q 30/02
H04L 29/08
G06F 16/907
G06F 16/9537
Abstract:
Inquiry data from one or more sources (e.g., client devices) may be analyzed to determine if key terms, date terms, and locality terms are indicative of an event to occur at a locality during one or more dates. Events that are detected may be communicated (e.g., via an electronic message(s)). An owner of a property may receive the electronic message(s) that are communicated for detected events and the owner may act to garner interest in stays at their property. Travelers searching for a property to stay at during the event may receive the electronic message(s) in the form of an offer (e.g., an email, a text message, a Tweet, a newsletter, etc.). The inquiry data may be received in real time and/or may be accessed from a data store. The Inquiry data may be curated to remove non-essential information and/or to include edited key terms, date terms, and locality terms.

Event Detection Using Inquiries

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US Patent:
20170180280, Jun 22, 2017
Filed:
Dec 17, 2015
Appl. No.:
14/973651
Inventors:
- Austin TX, US
Brent T. Schneeman - Austin TX, US
Assignee:
HomeAway.com, Inc. - Austin TX
International Classification:
H04L 12/58
G06Q 30/02
H04L 29/08
G06F 17/30
Abstract:
Inquiry data from one or more sources (e.g., client devices) may be analyzed to determine if key terms, date terms, and locality terms are indicative of an event to occur at a locality during one or more dates. Events that are detected may be communicated (e.g., via an electronic message(s)). An owner of a property may receive the electronic message(s) that are communicated for detected events and the owner may act to garner interest in stays at their property. Travelers searching for a property to stay at during the event may receive the electronic message(s) in the form of an offer (e.g., an email, a text message, a Tweet, a newsletter, etc.). The inquiry data may be received in real time and/or may be accessed from a data store. The Inquiry data may be curated to remove non-essential information and/or to include edited key terms, date terms, and locality terms.

Systems And Methods To Reconcile Free-Text With Structured Data

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US Patent:
20150286977, Oct 8, 2015
Filed:
Apr 7, 2014
Appl. No.:
14/247192
Inventors:
Brent Schneeman - Austin TX, US
Assignee:
Homeaway, Inc. - Austin TX
International Classification:
G06Q 10/06
G06F 17/30
Abstract:
The present application relates generally to systems, software and electronic commerce. More specifically, systems, methods and software to reconcile free-text with structured data are disclosed. Structured data may be in the form of a curated corpus. Free-text may be parsed and one or more terms, words, phrases or the like may be extracted by the parsing and compared with the structured data to determine if there is a difference between the structured data and the free-text it is compared with. Detected differences may be reported (e.g., to an endpoint) in real-time or near real-time and may include a suggestion or recommendation to change the free-text to more closely match the structured data or to change the structured data to more closely match the free-text, or both, for example. An endpoint may be a client device such as a smartphone, tablet, pad, or the like.
Brent Thomas Schneeman from Austin, TX, age ~58 Get Report