Analyst Intern Data

QUANYIN(KATHERINE) LIU

*** * **** **, **, New York, 10025

Phone: 917-***-**** E-mail: ************@*****.*** EDUCATION

Columbia University New York, NY

Master of Arts in Statistics Sep. 2022 - Present

Current GPA: 3.83/4.0

University of California, Santa Barbara Santa Barbara, CA Bachelor of Science in Applied Mathematics Sep. 2018 - Sep. 2022 Overall GPA: 3.6/4.0

PROFESSIONAL EXPERIENCE

Hungry Panda Ins. Santa Barbara, CA

Data Analyst Intern Jun. 2021 - Mar. 2022

● Cleaned around 2% missing data in 2k rows and transformed categorical variables to numerical using one-hot encoding for improving data clarity for subsequent analysis.

● Examine ad investment-revenue correlations via scatterplots in Python, applying linear regression analysis, and assessing model accuracy with Root Mean Square Error( RMSE ); Advised marketing team to prioritize WeChat channel and reduce indoor poster investments based on the outcome of regression analysis.

● Conducted an ANOVA to analyze the influence of purchase amounts within three groups of membership prices, utilized Tukey HSD test to identify significant differences between specific group pairs, and provided the marketing team with data-driven insights for optimal pricing strategies. Xiaocun Inc (Muncho) Santa Barbara, CA

Business Intelligence Analyst Jun. 2020 - Sep. 2020

● Conducted a Python-based data wrangling pipeline to extract district names from 1k-row address data using regular expressions.

● Apply log transformation and standardization techniques on revenue and purchase amount. Next, use bin edges to categorize Yelp ratings and create dummy variables for location. Then implement a random forest model to predict commission fees for new restaurants, enabling data-driven decision-making.

● Utilized boxplots to identify outliers, separated multi-value columns, and added pickup time and user wait time dimensions using SQL aggregation and grouping, streamlining data analysis .

● Utilized Tableau to create bar charts, analyzing the frequency of negative feedback tags across three sites and identifying a 30% rate for "missing/dropped food." Improved communication with drivers and enhanced takeaway packaging, effectively reducing this tag rate to 5%. Ernst & Young Beijing, China

Audit Analyst Jun. 2019 - Aug. 2019

● Designed a Python function to systematically rename unordered audit working paper photos using the "draft number + serial number" format, optimizing the organization of 500 images and enhancing productivity.

● Utilized Python to assess the continuity of 10,000 audit check voucher numbers, identifying and flagging any non-sequential vouchers for further investigation. ACADEMIC PROJECTS

Research Project in Data Analytics and Visualization Tableau Dec. 2021- Jan. 2022

● Employed a two-line chart in Tableau to compare total TV show and movie release trends from 2011 to 2020, revealing a decline in movie releases and an increase in TV show releases over the period.

● Visualized TV season output from 2011 to 2021 using a highlighted chart in Tableau, demonstrating Netflix's increased focus on new TV shows and producers prioritizing serialized programs. The chart also illustrated the growth of the TV industry and intensified competition over the past decade

● Created a bar chart to rank the top 10 TV show categories, demonstrating that international TV shows are the most popular category among viewers.

ADDITIONAL INFORMATION

Computer and Language Skills

Programming skills: SQL (MySQL), R (car, ggplot2), Python (Matplotlib, NumPy, Pandas, Scikit-Learn), Tableau Stats/ML: A/B Testing, Linear Regression, Logistic Regression, Tree-based Models (Decision Tree, Random Forest, XGBoost), Classification, Clustering

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