Data Analyst

Zhaoyan ZHANG

adb5cq@r.postjobfree.com j 617-***-**** j Santa Clara, CA 95051 *open to relocation SUMMARY

3+ years of experience in performing end-to-end data analysis with large data sets to generate actionable insights

Hands-on experience in product funnel analysis, marketing performance analysis and A/B testing to drive growth

Strong skills in SQL, Python (NumPy, SciPy, pandas, scikit-learn, matplotlib, seaborn), R, Tableau, Spark EXPERIENCE

GOSVEA San Jose, CA

Data Analyst Dec 2019 - Present

Mobile Ads Click-Through Rate (CTR) Prediction: Build ETL process, explore log data, perform data manipulation and visualization, engineer features and build predictive models (ML) to measure ads effectiveness via Python, Spark SQL and Spark ML GOOGLE - Google Ads Mountain View, CA

Quantitative Researcher (contract) Apr - Oct 2019

User Behavioral Analysis Using Web Server Log Data:

Identified multiple data sources, investigated Google Ads front-end data, checked data accuracy (missing data, inconsistent values, invalid data), designed table schema and core metrics

Performed quantitative analysis using SQL and Python to understand common and time-effective user journey

Figured out potential blockers to improve the user onboarding experience, delivered insights into web UI design

Experimental Design and Analysis:

Designed and analyzed experiments, conducted hypothesis test and pre-analysis to evaluate the impact of product changes through revenue (campaign lifetime revenue, first 28-days revenue), engagement (adoption rate, # of campaign activities, first 28-days churn rate) and productivity (campaign completion rate, construction time)

User Segmentation:

Aggregated data (600M+ rows) from multiple sources, improved data quality, performed exploratory data analysis (EDA)

Applied regression analysis, cluster analysis and user segmentation (industry vertical, spend tier, marketing objective, persona, and etc.) to obtain the feature usage patterns and find the growth opportunities

User Churn Analysis:

Identified primary churn reasons (performance-issue, revenue-issue, seasonal churn), assessed ads campaign performance (Avg. CPC, CPA, # of actions, lifetime value, re-activation rate)

Built and monitored dashboards, made recommendations for estimating a healthy churn rate and reducing unnecessary churn Obviously AI Berkeley, CA

Data Scientist Jan - Mar 2019

Database: Pulled and manipulated raw data via MySQL and performed ad-hoc analysis

Data Visualization: Created and tracked key metrics, illustrated insights in different easy-to-interpret visualizations

Machine Learning: Implemented end-to-end solutions to business needs, developed and refined ML models to predict DAU, LTV, retentions, conversions for SaaS companies via Python PROJECTS

Digital Campaign Performance Analysis:

Gained insights from game player dataset to understand player install-to-activation conversion and early purchase behaviors

Analyzed advertising campaign performance by marketing channel, estimated LTV and customer acquisition cost (CAC)

Customer Churn Prediction:

Developed machine learning models to predict and understand the drivers of success of subscription based on historical data

Performed problem definition, data collection, data preprocessing and feature engineering

Implemented Logistic Regression, Decision Trees, SVM, k-NN and XGBoost, evaluated model performance and achieved 0.94 precision

E-commerce Analysis on Amazon Prime Video Dataset:

Built predictive models to predict cumulated view time, generated business insights into video popularity and user engagement

Interpreted data, obtained feature importance, implemented LASSO and Ridge Regression, Polynomial Regression and Random Forest with hyper-parameter tuning, got 0.7621 model score EDUCATION

Worcester Polytechnic Institute Massachusetts

Master of Science in Statistics; GPA: 3.6/4.0 2016 - 2018 Beijing Normal University Beijing, China

Bachelor of Science in Economics; GPA: 3.5/4.0 2012 - 2016

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