Profile

MS in Business Analytics candidate at UC Davis. A data-driven, passionate, and goal-oriented fast learner with strong competency in Python and SQL. Value positions that I can contribute to, learn from, and grow with.

Skills: Data Wrangling, Data Visualization, Machine Learning, Hypothesis Testing, Experimental Design, Causal Inference Analysis, EDA, A/B Test, Time Series, Image Classification, Big Data, Business Intelligence

Technologies: MySQL, MS SQL Server, MongoDB, R, SPSS, Tableau, PowerBI, Python (Numpy, Pandas, Matplotlib, Seaborn, Scikit-Learn, SciPy, TensorFlow, PySpark), Advanced Excel, AWS, GCP, HTML

Certifications: AWS Cloud Practitioner, Tableau Desktop Specialist, SQL(Advanced)

Education

University of California, Davis San Francisco, CA

Master of Science, Business Analytics (currently 3.75/4.0) Expected Jun. 2023

Highlighted Coursework: Machine Learning, Advanced Statistics, Big Data, Data Management, Data Visualization

Award: Beta Gamma Sigma Membership (Top 20%)

Southwest University of Political Science and Law Chongqing, CHN

Bachelor of Economics, Economic Statistics (3.77/4.0) Sept. 2018 - Jun. 2022

Highlighted Coursework: Statistics, Data Mining, Time Series Analysis, Econometrics, Finance, Accounting

Professional Experience

Fashom Miami, FL

Data Scientist (Practicum Project) Sept. 2022 – Current

A fast-paced e-commerce startup planning to offer B2B API solutions regarding personalized recommendations.

Enhanced clothing attribute image classification algorithm accuracy by 40% by revamping model architecture using transfer learning (ResNetV2-50) within TensorFlow and utilizing Data Augmentation.

Extracted, preprocessed, and visualized 63k+ clothing inventory data from AWS Workspace, using SQL and Python (including pandas, numpy, matplotlib, seaborn, and requests)

Leveraged analytical storytelling to adeptly communicate with technical and non-technical stakeholders.

Improved team productivity by creating reusable Python functions and fostering knowledge sharing, resulting in streamlined workflows and increased efficiency.

PricewaterhouseCoopers (PwC) Shenzhen, CHN

Business Analyst Intern Sept. 2021 – Dec. 2021

Revealed valuable patterns and insights by leveraging MySQL, Python, and Tableau to extract, process, and visualize 27K + daily user engagement data from the client’s website.

Increased conversion prediction accuracy to 76% by applying Logistic Regression in Python to user engagement data, using significant features identified by Lasso Regression and business acumen.

Achieved an 84% accuracy rate in forecasting weekly conversions by developing an ARIMA model in R that utilized user engagement metrics, enabling proactive business planning.

Founder Securities Shenzhen, CHN

Industry Analyst Assistant Apr. 2021 – Jul. 2021

A well-known industry consulting company in China.

Revealed trends and seasonal patterns by performing EDA on 327K+ monthly sales records in the FMCG industry using Python and MySQL.

Identified opportunities and threats for the FMCG industry by conducting a SWOT analysis.

Contributed to 30-page industry reports with data visualization via Excel, summarizing key patterns.

Projects

Customer Repurchase Analysis (Python & R: Random Forest, Decision Tree) Causal Inference Analysis (Python: Causal Model) Social Network Analysis (PySpark, SQL) Image Compression (R: PCA) Default Prediction (R: Lasso Regression, Cross Validation) Clinics Check-In Analysis (Tableau) Web Scraping (Python: BeautifulSoup)

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