Yue Qian

Data Scientist specializing on ML modeling and automation

Shanghai, China

About

Experience

  • Data Scientist at PayPal
    Jun 2021 - Present · 5 yrs 2 mos

    Leveraged advanced ML modeling and GenAI to automate early detection and mitigation of fraudulent transactions, reducing financial losses from stolen card attacks. Built a Fully-Automated Fraud Risk Control Ecosystem • Spearheaded the development of an end-to-end fraud mitigation system using Unsupervised Learning, MMOE, and Reinforcement Learning, enabling 3-50 days earlier detection of stolen card fraud, which can save $XX million per year Reduced Stolen Card Loss by 30% YoY • Designed a custom tree-based algorithm tailored to PayPal’s use case, outperforming XGBoost with 190% higher recall at comparable precision ( U.S. Patent Appl. No. 18/282,468) Pioneered GenAI for Fraud Analytics • Automated fraud pattern reporting using GenAI, improving risk decision transparency and slashing report generation time from 1 hour to 1 minute Leadership & Collaboration • Self-driven problem-solver with a track record of identifying operational pain points and deploying scalable solutions. • Strong cross-functional leadership, successfully driving 0-to-1 projects from ideation to implementation. 2 * US Patent Application as First Inventor 2023 PayPal Spot Award Winner

  • Data Scientist at Destination Canada
    Jan 2019 - May 2021 · 2 yrs 5 mos

    Analyze card payment data, tourism arrival data, and marketing data from various channels to understand how travelers spend in different destinations in Canada and how to improve marketing to attract more visitors to Canada. ▪ Design database architecture and manage Oracle database to provide accurate data for the team ▪ Build data pipelines to automate data reporting, turning one-day work into one-minute work ▪ Build models using statistical and machine learning techniques to provide critical information for the industry ▪ Design data visualizations in BI dashboards which can be easily understood by non-technical audience ▪ Present data analysis results in the Travel and Tourism Research Association conference and inside the company, to provide meaningful insights to the industry ▪ Coordinate with people in four departments in the company to publish data on a monthly basis ▪ Design and provide training on several data topics, like data ETL and BI tools ▪ Help implement the transition in the company from working in different platforms to using a single BI platform

  • Data Analyst at Canadian International Resources and Development Institute (CIRDI)
    Sep 2016 - Oct 2018 · 2 yrs 2 mos

    Initially started as a volunteer in a capstone project and got hired after the project. Analyzed survey data from the artisanal mining industry to provide project managers in different teams at CIRDI insights about the current socio-economic environment and metallurgical techniques used in mining communities. Help them identify and develop future projects. ▪ Coordinated with the project managers to understand their objectives and requirements before data analysis ▪ Designed and applied data analytics according to the requirements and the availability of data ▪ Presented insights to the non-technical audience and provided suggestions for project development ▪ Led data analysis in the capstone project team, identified problems in data and solved the problems quickly

  • Data Scientist - UBC Capstone Project at Microsoft
    May 2018 - Jun 2018 · 2 mos

    In a three-member team, applied data analytics on traffic data and article data to identify features that influence traffic on MSN and built a model to predict future traffic. ▪ Created a data pipeline to predict future traffic. Tried regressions, ARIMA, and exponential smoothing ▪ Prepared and presented a report that outlined predictive features identified ▪ Experienced the NLP techniques, like LDA and TF-IDF, on article content

  • Data Analyst at Peter A. Allard School of Law at UBC
    Sep 2016 - Sep 2017 · 1 yr 1 mo

    Analyzed data about taxation and legislation in China to help a law school professor refine his research foci. ▪ Conducted statistical analyses and communicated key findings in response to questions from the professor ▪ Did clustering analysis (K-Means & Hierarchical), principal component analysis, and regressions in R