Hi everyone! My name is Shyam Sundar and I am currently VP Engineering at Le Tote, where I lead a team of 35 people. Looking forward to meeting you!
Hey, I'm available every Friday at 9:00 PM (GMT)
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July 31, 2020
9:00 PM (GMT)
VP Engineering and product data science
Aug 2018 - current
I lead threat detection and intelligence at Proofpoint. We operate at the intersection of data products & cyber security, responsible for protecting more than 60% of the fortune 1000 companies from cyber security attacks. In short, we make the internet a safer place for everyone!
Jul 2017 - Jun 2018
Led engineering, dev ops, data science and data engineering. Le Tote is a personalized online subscription service ("Netflix for fashion") that connects people to their fashion needs based on billions of data points. It was a great learning experience working in a startup but the funding situation led to major cuts in the engineering organization. The company has raised more than $60M from top-tier venture capital firms including Andreessen Horowitz, Google Ventures, Y Combinator, Azure Capital and Sway Ventures.
\- Created Le Tote's first data science program which improved personalization by ~15% by leveraging cutting edge deep learning techniques
\- Rolled out an engineering operational excellence program which reduced business critical issues by more than 66%.
\- Helped international expansion from US to multiple countries (including China)
\- Helped expand fulfillment software to handle multiple fulfillment centers.
\- Revamped organizational structure to reinforce ownership and autonomy to teams
Director of Engineering, Data & Search
Dec 2014 - Jul 2017
I was responsible for the following programs at Zendesk (San Francisco and Melbourne, Australia):
1\. Data Products: Power game changing features on zendesk with predictive modeling and data science using customer behavior data.
2\. Data reporting platform: Help businesses gain insights from all aspects of customer relationships captured in Zendesk products (ticketing, chat, voice etc). This unified data platform ingests real time data, processes it using google data flow and stores in for analysis in big query.
3\. Internal Product analytics: Help internal teams slice and dice data and make informed decisions through the product data warehouse.
4\. Search Platform: The unified search service which supports all of Zendesk's products.
5\. Search relevance & ranking: Help improve search relevance & ranking based on machine learned models from customer behavior data.
6\. Customer health: A machine learning system that calculates a customer health score based on usage patterns and trends over a period of time, to help reduce churn.
Senior Software Development Manager
Dec 2012 - Nov 2014
Grew a team from scratch to help manage Rackspace's cloud. These products have fundamentally changed the way Rackspace provides fanatical support to customers.
Unified ticketing: Designed and developed a ticketing system to manage customer issues for different parts of Rackspace’s cloud services and dedicated hosting. This high performance, globally distributed system was developed using open stack and open source technologies.
Cloud control: Designed and developed this dashboard to create a one stop aggregated view of 20+ cloud products for Rackspace’s support Engineers. This tool helped improve productivity of cloud support Engineering by as much as 40%
Software Development Manager
Oct 2005 - Dec 2012
Worked on products to help understand the impact of product data on customer behavior and help transform Amazon's catalog the most authoritative and comprehensive on the planet. Was lucky to apply data science and data engineering to solve real world problems, before they became buzzwords in the industry. Started out as a software development engineer and transitioned into a software development manager at Amazon.
\- Developed a data score to help surface products with superior quality of data across the entire Amazon catalog (> 1 billion items) which helped improve key search metrics like abandonment rate, query group click rate and reformulation rate.
\- Managed the crowdsourcing program and improved Amazon’s catalog data by 10 million product data corrections
\- Improved Amazon’s data selection algorithm to pick the “richest’ data value among the set of merchant data contributions which helped more than 3 million products.
Designed and managed the system responsible for measuring the extent of duplication and misclassification in the Amazon catalog which was used by Bezos’ weekly business review.
\- Architected & developed this system to improve attribute based navigation in Amazon search & browse pages. Improved brand quality by about 6 times which significantly helped product discovery on the Amazon website.