Zihao (Hector) Zhao
Senior Data AnalystAction-oriented Senior Data Analyst with over 5 years of experience in the digital entertainment industry building scalable data pipelines, advanced statistical models, and executive dashboards. Additionally brings entrepreneurial expertise from founding and scaling a profitable wholesale business, possessing a deep understanding of full-cycle business operations, supply chain management, and data-driven customer acquisition.
6
yrs_experience
6
roles
38
skills
0
dashboards
Experience— 6y total
- ›Architected and deployed 200+ scalable data processing pipelines using advanced SQL, enabling efficient large-scale dataset manipulation, storage optimization, and cross-functional revenue trend investigations to solve 98% of complex data inquiries.
- ›Developed 150+ executive-ready Tableau dashboards, empowering 80% of product managers with intuitive data visualizations to drive proactive business decisions and effectively diagnose system issues.
- ›Built and governed over 20 core KPI frameworks to accurately assess in-game economy health, systematically identifying inflation risks and accelerating proactive decision-making for leadership teams.
- ›Led pre- and post-launch analytical support for 3 major titles, executing multiple complex ad-hoc analyses that contributed to exceeding internal targets and achieving over 50% Day 1 retention on iOS.
- ›Developed and implemented a scalable level optimization methodology that directly improved player VC spend patterns, resulting in an approximately 20% increase in DB VC spend while maintaining healthy engagement.
- ›Founded and operated a one-person outdoor products wholesale business, driving rapid growth to achieve $140,000 in revenue by the second year.
- ›Acquired and served over 100 local B2B enterprise clients, maintaining strong customer relationships and ensuring high satisfaction and retention.
- ›Managed end-to-end business operations including supply chain management, inventory and warehouse management, and strict tax compliance.
- ›Spearheaded customer acquisition and brand presence through targeted social media operations and frontend digital optimization.
- ›Engineered scalable A/B testing evaluation frameworks and proposed database infrastructure improvements for analytics taxonomy, streamlining experiment analysis, ensuring metric consistency, and saving teams 2+ hours weekly while guiding product strategy.
- ›Proposed and implemented database infrastructure improvements for analytics taxonomy, ensuring metric consistency and streamlining deep analyses for 3 new games.
- ›Resolved 25+ complex data requests from product and engineering teams each quarter using advanced SQL, translating trends into actionable cross-functional insights.
- ›Sourced and managed large external datasets via open APIs, applying NLP and scripted scraping to uncover user sentiment trends and proactively guide acquisition strategies.
- ›Investigated declining profitability in a flagship product by establishing comprehensive revenue and engagement funnels, decomposing factors, and effectively visualizing metrics to save 10+ manual hours weekly.
- ›Performed user attrition analysis by creating 150+ features and developing predictive machine learning models to identify churn likelihood, reporting 10+ core signals to guide mobile strategy.
- ›Revamped database schemas and wrote high-quality data pipelines to evaluate user engagement, resolving four major infrastructure bottlenecks with the push notification system.
- ›Created a game currency value and inflation evaluation framework to assess in-game economy health, identify inflation risks, and reduce ad-hoc economy research time by one hour weekly.
- ›Conducted a competitive analysis covering four existing competing products regarding mobile game onboarding tutorial and provided five recommendations for improvement, guiding game design.
- ›Established a multifunctional dashboard using open source Python packages as a potential substitute for Tableau to visualize over 40 key metrics evaluating performance of interstitial Ads.
- ›Designed a new metric called rolling weekly DAU retention rate, capable of capturing reactions of users in different categories toward in-game events on a rolling basis, contributing directions for UA strategies.
- ›Analyzed consumption patterns of consumers in the Bay Area and created optimized development plans for 4 cities, accurately predicting market growth based on seasonal data trends.
- ›Negotiated with more than 50 small business owners and established 20+ partnerships, boosting product variety by 10% and monthly sales by 15% through data-driven promotional plans.
- ›Actively planned optimal routes for food delivery drivers, utilizing analytical skills to maximize operational efficiency and ensure timely fulfillment.
Skills
Data Engineering & Programming
Advanced SQLPythonSparkRSASScalable PipelinesLarge DatasetsHTMLCSS
BI & Visualization
TableauLookerExecutive DashboardsKPI GovernanceReal-Time AlertsPlotly
Data Analysis & Methodology
A/B TestingStatistical ModelingForecastingExploratory AnalysisDeep Trend InvestigationLinear Optimization
Machine Learning
NLPPredictive ModelingRandom ForestFeature EngineeringBoosted TreesNeural NetworksK-nearest Neighbors
Database Infrastructure
BigQueryPostgreSQLMongoDBMySQLSchema Management
Business Operations
Supply Chain ManagementInventory ManagementCustomer AcquisitionSocial Media OperationsCRM
Projects
Identity Fraud Detection
Designed a comprehensive fraud detection solution on 100,000 credit card application records. Created 680+ features and built 5 classification models (Boosted Trees, Random Forest, Neural Network, KNN), capturing 54% of fraud activities.
PythonMachine LearningFeature EngineeringRandom Forest
Humana-Mays Healthcare Analytics Competition
Explored and cleaned longitudinal data with 800+ features and 60,000+ observations to build a binary classification model forecasting transportation issues for 16,000+ members. Achieved top 50 rank nationwide with F1-score of 0.85.
PythonBinary ClassificationPredictive Modeling
King's Hawaiian Marketing Analytics
Analyzed marketing data from 50+ properties and 70,000+ observations. Built a linear regression model explaining 81.9% of marketing ROI variance and visualized volume sales boosted by 9 marketing activations.
PythonSQLLinear RegressionA/B Testing
Education
University of Southern California
May 2022Master of Science / Business Analytics
GPA 3.8Fall 2020 Dean's List
University of California, San Diego
Jun 2019Bachelor of Science / Management Science
GPA 3.6
Certifications
Data Analysis in Spreadsheets
DataCamp · Aug 2020
Customer Segmentation in Python
DataCamp · Oct 2020
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