David J Magar from Seattle, WA, age 83

Resumes

Senior Program Manager

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Location:

Seattle, WA

Industry:

Computer Software

Work:

Microsoft
Senior Program Manager
Amazon
Senior Product Manager - Alexa Shopping
Microsoft Jul 1, 2015 - Aug 2017
Senior Program Manager - Microsoft Azure Stack
Microsoft Jan 2014 - Jun 2015
Program Manager - Bing's Backend For Cortana on Windows 10
Microsoft Oct 2012 - Dec 2013
Program Manager For the Azure Sql Reporting Team

Education:

Tel Aviv University 2006 - 2014
Master of Science, Masters, Electrical Engineering Tel Aviv University 2001 - 2004
Bachelors, Bachelor of Science, Electrical Engineering

Skills:

Cloud Computing
Integration
Software Development
Product Management
Business Intelligence
Software Engineering
Software Project Management
System Architecture
Security
Microsoft Sql Server
Agile Methodologies
Team Leadership
Program Management
Execution Skills
Project Management
Systems Engineering
Mobile Applications
Embedded Systems
Product Requirements
Agile Project Management
Technical Leadership
Software Design
Enterprise Software

Languages:

English
Hebrew
French

David Magar

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Work:

David's Plumbing Services 2009 - 2013
Owner

Senior Program Manager

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Location:

Seattle, WA

Work:

Microsoft
Senior Program Manager

David Magar

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David Magar

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Us Patents

Unusualness Of Events Based On User Routine Models
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US Patent:

20160321616, Nov 3, 2016
Filed:

Sep 25, 2015
Appl. No.:

14/866338
Inventors:

- Redmond WA, US
David Magar - Sammamish WA, US
Michael Wascher - Redmond WA, US
Richard Zhao - Kenmore WA, US
Suryakant Choudhary - Redmond WA, US
International Classification:

G06Q 10/10
G06F 17/30
Abstract:

In some implementations, sensors provide sensor data reflecting user activity detected by the sensors. An event analyzer generates an unusualness score for an event associated with a user based on routine-related aspects generated from one or more user routine models associated with the user. The one or more user routine models are trained based at least in part on interaction data comprised of the sensor data. Event attributes of the event can be received that include a time of the event and attendees of the event. The unusualness score may be generated by analyzing the event attributes with respect to the routine-related aspects. The unusualness score is generated to quantify a level of deviation between the event attributes and the routine-related aspects. Service content can be generated for the user based at least in part on the unusualness score generated for the event.