Summary
Overview
Work History
Education
Skills
Timeline
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Zhongkun(Chris) Jin

Bellevue,WA

Summary

Staff Machine Learning Engineer specialized in the Fintech industry and built Machine Learning solutions with one of the world's largest financial datasets. Lead the development of data intensive application and products throughout their entire lifecycle via skillsets across data analytics, data engineering, machine learning, and AI development. Experienced leader via strong tracking record of leading cross-functional project with successful outcome delivered.

Overview

6
6
years of professional experience

Work History

Staff Machine Learning Engineer

Plaid Inc
01.2019 - Current
  • Tech lead for Plaid's risk defense data team. Build an end to end ML powered risk defense team defending Plaid against account take over (ATO) risk. This system has reduced the ATO rate by over 50% while increasing the conversion by 2%.
  • Build a Security Notifications system that serve as the primary feedback loop for Plaid's risk defense ML models, allowing the team to objectively evaluate the system and retrain the system to sustain the performance over time.
  • Define and continually track Plaid's primary risk KPI, Suspect ATO rate, which is reported to Plaid's Chief Security Officer.
  • Tech lead for Plaid's Transactions, Investments, and Liabilities products.
  • Build Machine Learning Powered product features, such as transaction classification and transaction named entity recognition that serve as key differentiating factor for Plaid's Transactions product.
  • Developed a cross-team partnership, tracking 9 projects and leading to successful execution
  • Led the development and scaling of the Recurring Transactions Product, which now generates 500k ARR.
  • Led the adoption of a new serving infrastructure that results in 20% latency reduction for model inference and 40% cost savings
  • Initiated a cross-functional partnership for labeled data generation, leading to a successful pilot job launched with our Support function
  • Enhanced Transactions product reliability, reducing SEV detection time and frequency significantly by revamping Transactions SLOs to align them closely with customer-perceived quality and
  • Maintained over 99.9% uptime for key ML models and services, optimizing cost efficiency
  • Led the deprecation of legacy services, simplifying technical architecture and realizing significant cost savings
  • Co-developed a comprehensive analytics suite, aligning closely with product health metrics and SLOs
  • Solved long-standing security normalization issues, achieving a >99.9% Investments data pipeline success rate
  • Advocated for migrating investments account typing logic, enhancing operational efficiency
  • Launched a Product Reliability Audit Scorecard, achieving 92.5% completion of the associated OKR
  • Advocated for and drove the integration of Pinecone for vector search functionality, powering the Merchant Search functionality within our Enrich product
  • Developed a ML model retraining pipeline for key Transactions models, achieving sustainable quality for the Transactions product

Education

Master of Professional Studies - Applied Statistics

Cornell University
Ithaca, NY
05.2018

Bachelor of Science - Statistics

University of California, Davis
Davis, CA
03.2017

Skills

  • GRPC services
  • Distributed systems
  • Product analytics
  • Spark
  • Python
  • PyTorch
  • Golang
  • LLM application development
  • Hadoop
  • AWS
  • JavaScript

Timeline

Staff Machine Learning Engineer

Plaid Inc
01.2019 - Current

Bachelor of Science - Statistics

University of California, Davis

Master of Professional Studies - Applied Statistics

Cornell University

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Zhongkun(Chris) Jin