Huafeng (Hua) Zhang
Coding: R, Python, SQL
Statistics: Power Analysis, Experimental Design & Sampling, ETL Data Transformation, Data Visualization, A/B Testing, Clustering, Regression Modeling (e.g. OLS), Mediation Analyses, Time-Series Modeling, Survey Design, Natural Language Processing
Business: Strategy Planning, Research Design and Prioritization, Project Management, Leadership, Cross-functional Collaborations, Influencing non-technical Stakeholders, Adaptable, Listening with Empathy, DEI Awareness
Montana State University
B.S. Mathematics - Statistics (GPA: 3.8)
Minor in Economics (GPA: 3.8)
Google: Kudos (8), Peer Bonus (5) & Spot Bonus (9)
Additional Info
• Completed graduate level statistics courses on sampling, experimental design, probability theory
• Acquired practical data science skills through completion of courses on DataCamp and Coursera
• Proficiently bilingual in both Chinese and English languages
Quant Research Analyst III · Google LLC · 
Seattle, WA
07/'18 - Present

  • Drove long-term strategies to improve over 100M users' experience in TV & Movie journeys by effectively influencing product leads to act on foundational global user insights on Google Search

  • Ensured equitable compensation by leading Google's Annual Pay Equity program in 2020. Insights from statistical analysis were reviewed by Google's top leadership.  Final adjustments based on the analysis directly impacted over 120K Google employees' annual compensation

  • Led mixed methods (including mediation analysis, time-series modeling & survey analysis) research on hiring, performance reviews and internal mobility to help program owners design more inclusive and effective people processes

  • Empowered auditors, program managers, and product managers to gain data insights and to visualize findings through advanced analytical tools with a user-friendly "one-click button" solution in a dashboard and Python notebook preview

  • Hosted data trainings and statistical learning sessions to enable auditors and people analysts to work independently with data 

  • Fostered community contributions by interviewing and mentoring junior analysts as well as volunteering at various team events

  • Recognized with a Superb rating, placing in the top 2% of all employees

Data Scientist · CityBldr · 
Seattle, WA
10/'17 - 06/'18

  •  Led projects on translating unstructured information into interpretable features for CityBldr's machine learning pipeline by utilizing NLP techniques such as Naive Bayes and Topic Modeling
  • Initiated efforts to develop comprehensive models of extracting business insights by combining data from various sources 
  • Created insights using multivariate data analysis to inform company strategy and public communication messages, and presented results to engineering, project management and sales teams

Predictive Modeling on Refugees' Online Learning Behavior

Applied a mixed effects logistic regression approach combined with advanced Natural Language Processing (NLP) methods to gain profound insights into the online learning behavior of refugees. This comprehensive analysis aimed to enhance support systems and increase their success rates in passing citizenship tests 

Financial Health of United States Banks in 2016

Employed k-means cluster analysis in R to precisely identify all failed banks amidst the tumultuous 2008 financial crisis

Analysis of Website Traffic Data

Leveraged Google Analytics API to collect traffic data; identified optimal maintenance days for web developers using ANOVA test and Tukey‐Kramer test