Data Analyst

ANDY WU

E-mail: *******@*****.***

Address: ***** ***** **, ******, ** 94560 Cell Phone: ( 408) 595- 8667 _

SUMMARY Seasoned veteran and proven leader in the field of Business Analytics, Data Analytics

& Engineering, solid foundation in math and computer programming, diverse background & expertise in modeling, analysis and reporting. Deep understanding about finance & accounting:

1.Problem solver with strong product sense and business acumen, and proven track records providing analytical supports to engineering, operations, marketing, finance, risk, legal, compliance, and human resource stakeholders 2.Direct experience with building and productionizing machine learning models, ETL pipelines, designing and aligning business and product metrics, setting up and analyzing A/B test experiments, mining actionable insights from rich data environments, and presenting results and recommendations to technical as well as non-technical audience

3.Ability to execute under ambiguity, handle semi-structured data sets, with minimal guidance, assistance, and documentation, deliver robust and scalable MVPs 4.Hands-on with scripting languages and analytical tools such as Python, SQL, Presto, Hive, R, Excel, Tableau, and Superset, etc. 5.Extensive experience building, leading, motivating and growing data teams and projects at scale, mentoring and motivating data scientists, data analysts, business analysts, data engineers, and data infrastructure engineers, at all levels from interns to managers and directors.

WORK BQ Realty Group Newark, CA

EXPERIENCE Real Estate Agent 2024 – present

Coupang, Inc.Mountain View, CA

Director of Data Analytics, Search & Discovery 2021 – 2024

● Worked with product managers and managed Search Product Analyst in US and international offices, hired and trained 10+ new analysts in 2 years Wish (dba ContextLogic) San Francisco, CA

Director of Engineering, Head of Data Platform & Analytics 2016 – 2021

● Led Wish Data Engineering, Data Infra Development, Data Science & Analytics. Built a global team of 30+ data professionals from scratch that has been providing analytical excellence to all the functional departments: o Architected and built corporate data warehouses, running and maintaining the core pipelines that copy data from MongoDB collections to Hive tables

(transactions, users, merchants, products, etc.), which were used by the entire company for production jobs as well as data analytics o Deployed and manage analytical services such as Airflow, Tableau, Superset, develop user friendly add-on features, and design usage policies and promote best practices

o Managed the development of an in-house data lake on AWS, using open source solutions such as TD-agent, Kafka, Flink, Presto, Spark, etc.

● Led the development of e-commerce risk platform and its applications ($200M+ impact to date):

o Productionized a consumer payment fraud detection model that increases conversion and controls fraud rate

o Implemented a real-time feature store using Graph DB o Built detection models for major merchant fraud patterns, including false advertising, counterfeits, fake tracking, deceptive fulfillment, etc. o Built refund abuser, and promo code abuser detection algorithm o Built fake rating / review detection algorithm and purified rating metrics o Built bot detection and ATO detection algorithms using user behavior analysis o Initiated and has been supervising the Merchant Payment Risk Audit process which has so far protected $100M+ funds from fraud loss o Built macro fraud trend monitors and share weekly insights with management

● Led data science projects on Merchant Growth & Diversification ($100M+ impact to date)

o Built “Power User” models and optimized feed rankings to drive merchant / product diversification goals

o Built Product listing optimization tools and ran pricing optimization, image optimization, ranking / impression optimization experiments o Built an external intelligence gathering / competitor analytics tool, used by new product ranking, pricing optimization, and business development ops

● Led data science projects on Supply Chain & Logistics Optimization ($100M+ impact to date)

o Built product recommendation and inventory planning algorithms for Wish owned inventory programs, and Wish Local forward deployment programs o Built inventory distribution algorithms for Fulfilled By Wish (FBW) programs o Built Wish Local store ranking algorithm, store value prediction and new store acquisition recommendation engine

● Led development of the Financial Audit platform and FP&A reporting system, a critical financial metrics portal for Wish IPO process and earning releases Meta Platforms, Inc.Menlo Park, CA

Lead Data Scientist, FP&A 2015 – 2016

● Worked on short-term and long-term Ads Revenue Forecasts in R, and stock price predictions using competitor analysis

● Led a team of data scientists, BI engineers, and financial analysts to build the revenue analytics data framework from ground up, shortened the revenue closing process from 5+ days to 1 day, and delivered the highly confidential revenue reporting tool for the CFO and upper management

PayPal, Inc.San Jose, CA

Manager, Global Merchant Analytics 2013 – 2015

● Merchant retention funnel analysis and churn prediction using Logistic Regression

● Modeled site latency impact on payment conversion / revenue and customer experience / churn, using Logistic Regression, Random Forest

● Developed key Merchant KPIs (Payment Volume, Revenue, Take Rate, Mobile Penetration, etc.) reporting framework and dashboards that were used by upper management and regional sales teams

FocusKPI, Inc.Campbell, CA

Analytics Consultant 2011 – 2015

U.S. Bank Cincinnati, OH

Financial Engineer 2006 – 2010

● Created auto leasing residual risk forecasting models based on Monte Carlo simulation, which helped establish the residual loss provision that ensured the business to stay solvent during the collapse of auto leasing industry in 2008, when major competitors such as Chrysler Financial and Wells Fargo completely halted their leasing businesses

● Created credit risk forecasting models based on Logistic regression for Consumer Lending products including student loans, auto loans / leases, mortgages, mobile home, HELOC, which were used by Risk Management and Pricing departments EDUCATION Vanderbilt University Nashville, TN

Master of Science in Computer Science 2006

University of Toronto Toronto, Canada

Master of Science in Statistics 2004

Peking University Beijing, China

Bachelor of Science in Statistics 2003

STRENGTH Machine Learning, Statistical Analysis, Forecasting, Simulation, Big Data Analysis; AND SKILLS Data Platform, Data Engineering, ETL, Pipelining; Airflow, Tableau, Superset; Python; SQL, Presto, Hive; MongoDB; Redshift, Teradata, Vertica; R, SAS; Excel; A/B Testing; Anomaly Detection; Data Cleansing; Visualization, Dashboarding; Fraud Detection; Risk Management; Business Acumen; Vendor Management; Finance, Accounting; Chartered Financial Analyst (CFA). Real estate, real estate investment, real estate finance Recreational swimmer, ski & snowboarding, teaching sports PSIA Alpine Level 1 Instructor; Children’s Specialist 1; Passed Level 2 Ski Exam

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