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Greg Linden

Research Software Engineer @ Microsoft

mostly retired internet relic

Seattle, Washington

Ranked #209 out of 4,183 for Research Software Engineer in Washington

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Greg Linden's Email Addresses & Phone Numbers

Greg Linden's Work Experience

Microsoft

Research Software Engineer

January 2008 to April 2009

Amazon.com

Manager

March 1999 to February 2002

Amazon.com

Software Engineer

February 1997 to February 1999

Greg Linden's Education

Stanford University Graduate School of Business

MS, Management

2002 to 2003

University of Washington

MS, Computer Science

1994 to 1996

UC San Diego

BA, Computer Science & Political Science

1990 to 1994

Greg Linden's Professional Skills Radar Chart

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Reflective

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Greg Linden's Estimated Salary Range

About Greg Linden's Current Company

Microsoft

I had an unusual opportunity to work across Microsoft on search relevance, advertising relevance, A/B testing, scalability, performance, large scale data analysis, personalization, and recommendations, discovering opportunities worth hundreds of millions of additional revenue. Teams I worked with included Bing Relevance, Bing Performance, Bing Personalization, Bing Ads, Microsoft Research, Corporate Strategy, and incubations both in and outside...

Frequently Asked Questions about Greg Linden

What company does Greg Linden work for?

Greg Linden works for Microsoft


What is Greg Linden's role at Microsoft?

Greg Linden is Research Software Engineer


What is Greg Linden's personal email address?

Greg Linden's personal email address is g****[email protected]


What is Greg Linden's business email address?

Greg Linden's business email addresses are not available


What is Greg Linden's Phone Number?

Greg Linden's phone (206) ***-*101


What industry does Greg Linden work in?

Greg Linden works in the Internet industry.


About Greg Linden

ūüďĖ Summary

Research Software Engineer @ Microsoft I had an unusual opportunity to work across Microsoft on search relevance, advertising relevance, A/B testing, scalability, performance, large scale data analysis, personalization, and recommendations, discovering opportunities worth hundreds of millions of additional revenue. Teams I worked with included Bing Relevance, Bing Performance, Bing Personalization, Bing Ads, Microsoft Research, Corporate Strategy, and incubations both in and outside of Live Labs. From January 2008 to April 2009 (1 year 4 months) Manager @ Amazon.com By 1999, Amazon was well into its "Get Big Fast" era, entering many product lines outside of books, launching international websites, and creating efficient shipping warehouses around the world. It was still popular at this point to claim online retailing was just a fad (such as the "Amazon.bomb" article). Notable around this time was that Amazon was early and often the first to develop techniques that are taken for granted now, such as fleets of commodity webservers and NoSQL databases, launching early and often, personalization and recommendations, and optimizing websites using log analysis and A/B testing.I built and led a team of 25 people developing personalization and recommendations features for Amazon.com. These features change almost every major page on the website to be unique to each person, are used by millions of people, and yielded billions in revenue. This team also built the ref tag system for metrics, revenue credit assignment, and online experimentation, as well as iquitos, which was the beginning of Amazon's microservices architecture. In this role, I was able to be part of developing the personalization vision for Amazon.com and had regular monthly meetings with Jeff Bezos. From March 1999 to February 2002 (3 years) Software Engineer @ Amazon.com Twenty years ago, in the early days of e-commerce, Amazon.com only sold books and only had a US website. In early 1997, Amazon.com had only one webserver, only one database, and only one warehouse. This was before Javascript, before CSS, and well before mobile and smartphones. Netscape was the most popular web browser, but most people didn't use web browsers or e-mail yet. Those that did often feared to enter their credit card on Amazon.com, preferring to call in (on a landline). A terabyte of data was a lot (drives were 16G), and most other companies threw away logs rather than trying to even store and analyze them.Much of the work during this period was scaling and growing Amazon.com, adding new product lines, and expanding internationally. I was a major contributor to the architecture, scaling, performance, and optimization of Amazon.com's early website, web servers, and databases, and was a founding member of the Amazon Bar Raisers.I also developed most of Amazon's early personalization features. I was the primary inventor and developer of the Amazon.com recommendations engine, which is directly responsible for billions of dollars of incremental revenue for Amazon.com. I optimized, improved, and extended Amazon's well-known Similarities feature ("Customers who bought X also bought"). From this work, I have 32 patents on recommendations, search, and personalization, and am considered the first inventor of the now widely used item-to-item collaborative filtering algorithm. From February 1997 to February 1999 (2 years 1 month) Data Scientist, Experimentation in AI & Research @ Microsoft A/B testing and online metrics seeking usability improvements on nearly every Microsoft product to help hundreds of millions of customers.Researched long-term harm, including adjusting short-term metrics for long-term effects, and methods for maximizing long-term revenue. Developed novel techniques for experimentation to overcome dilution from cookie-based experiments and properly measure long-term effects. Uncovered costly underestimation of the harm caused by low quality advertising.Advised many groups across Microsoft on recommender systems in news, search, advertising, and other products, focused on the practical issues of building deep learning and machine learning systems that best help humans.Analyzed petabytes of log data to discover strong frustration signals. Investigated poor correlation of offline accuracy with online metrics, sensitivity of human judgments to the question asked, reliable ground truth, and relationship of visit frequency to more sensitive signals, leading to changes that ultimately improved usability and growth.Part of leading the Analysis & Experimentation team, helping grow, manage, and set the priorities of a group of ninety people with a budget in the tens of millions and broad impact across Microsoft. Regular meetings with Microsoft executives. From January 2016 to March 2018 (2 years 3 months) Bellevue, WASoftware Engineer @ Google Improved and substantially increased usage of tools for machine learning, data science, and deep learning at Google. I left because I wanted to have a bigger impact on customers. From June 2015 to October 2015 (5 months) Seattle, WAFounder @ Geeky Ventures Used by millions of people around the world, including in coding camps and computer labs at schools, Crunchzilla offers game-like tutorials that introduce children and adults to computer programming. From September 2009 to June 2015 (5 years 10 months) Founder @ Findory It may be difficult to remember now, but, in 2003, newspapers still questioned whether they should make their content available on the Web. Online, most newspapers published the same content as their print version and updated infrequently. Back in 2003, the idea of showing a personalized front page, with different content for different people and with news updated in real-time, was radical and controversial.I founded and built Findory, a popular personalized news website used by hundreds of thousands of people that picked news stories based on what each reader read in the past. Findory developed one of the first hybrid recommender systems, combining content analysis and behavior data to help people find and discover interesting news articles. Early for its time, Findory's recommender algorithm optimized for helping people discover information including promoting diversity of viewpoints and countering spammers and other adversarial agents. Findory was acquired by Microsoft in 2007. From October 2003 to November 2007 (4 years 2 months)


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In a nutshell

Greg Linden's Personality Type

Introversion (I), Sensing (S), Thinking (T), Perceiving (P)

Average Tenure

2 year(s), 8 month(s)

Greg Linden's Willingness to Change Jobs

Unlikely

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