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Trust And Safety Backend Introduction- Mercari India DEV Meetup #01 Backend

mercari
PRO
September 01, 2022

Trust And Safety Backend Introduction- Mercari India DEV Meetup #01 Backend

WE ARE HIRING!!
https://careers.mercari.com/hello-india/

This is a team introduction of Trust and Safety (TnS) team.
Trust and Safety (TnS) refers to monitoring, detecting, and handling prohibited behavior, including fraud, to ensure that Mercari users have a safe and secure experience. TnS in Mercari is not only implemented by the Customer Service (CS) Team which detects and handles such matters, but also by the TnS Team which is developing a platform that makes use of machine learning.

- Speaker Profile
Nikinsha Kesharwani
After graduating from university, worked in a major network company as a software engineer. Joined Mercari in 2019, and has since worked in the Trust and Safety domain as a software engineer.

This slide was presented at the first Mercari India DEV Meetup on the 20th August to introduce the Backend teams of Mercari group. The recording can be viewed from the link below.
https://youtu.be/0hDbM-LDSbE

Please follow us on our LinkedIn account for the latest information!
https://www.linkedin.com/company/mercari-india/

#Engineering #MercariIndia #Backend

mercari
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September 01, 2022
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Transcript

  1. 1 Trust And Safety Backend Introduction By Nikinsha Kesharwani Technical

    Lead
  2. 2 󰠁 Software Engineer on the Trust and Safety team


    
 🧘 From India
 
 🏯 Joined Mercari in Feb. 2019, 3.5 years in Japan
 
 🍲 Hobbies include cooking and playing badminton 🏸
 
 Nikinsha Kesharwani ✨

  3. 3 TnS ¥1000,000 ¥90,000

  4. 4 Some types violations in market Items that violate the

    law XXX-XXX Offensive comments Please transfer the money to my bank account XX-XX-XX Payment not provided by Mercari Foods nearing expiration date
  5. 5 2 types of Moderation • Listed item moderation •

    Account moderation
  6. 6 Why do we need item moderation? • 20.4 million

    MAU browsing and listing items. • More than 1.5 million items listed per day. • Proactive detection of violating items using technology is necessary.
  7. 7 Our approach for Item moderation Fill in the information

    Complete listing Tap “List” Detection + Moderation Prevention
  8. 8 Overview of Item moderation Rule based system ML System

    Automatic delete CS decision 2. After Listing Edit Rule based system 1. Before Listing Rule based + ML model Rule based warning/stop New Listing
  9. 9 Overview of Item moderation Mod Tool Operator Rule ML

    Rights Holder Customer Item Detection Internal External Rule and ML based system are monitoring all items listed by 20.4 million active users
  10. 10 Architecture of Item moderation system Gateway Mod Tool Listing

    Service Reporting worker ML System Rule based System List item Subscribe Publish events (Detection) Subscribe Publish Publish Subscribe Report Item Seller (Prevention)
  11. 11 Account moderation offensive comment! Warn and restrict! 警告と禁止! CS

  12. 12 Overview of account moderation • Major violation that are

    being detected ◦ Detection with user information and behaviour ▪ listing not at hand items
  13. 13 Tech Stack • Backend Services (6) ◦ Golang, GCP

    technologies like spanner, cloudSQL, pub/sub etc. • ML Service (1) ◦ Python, sklearn, and kubeflow • Frontend Service (1) ◦ TypeScript and React • Build and release ◦ Docker, Kubernetes, Spinnaker
  14. 14 What do I enjoy • Working in ◦ New

    technologies. ◦ Cross-functional team, with opportunities to work on front-end and ML. ◦ Great work culture, people and work life balance.
  15. 15 People we would love to work with • Resonates

    with our mission to “Create safe marketplace using technology”. • And work together to continuously enhance safety and security of Mercari marketplace.
  16. 16 Thank you! ありがとうございます