Machine Learning Data Science

Shutai (Frenkie) Li

Master of Information System students with 1+ years of experience in data science and consistently leveraging data (using tools like Python, SQL & ML) to break down the “So What?” into actionable insights, and driving strategic outcomes.

EDUCATION

Carnegie Mellon University Pittsburgh, PA

Master of Science in Information Systems (Business Intelligence Stream) Aug 2024 - Dec 2025

- Academic: Cumulative GPA 3.5/4.0

- Relevant Courses: Machine Learning for Problem Solving; Database Management; Advanced Business Analytics Central University of Finance and Economics Beijing, China Bachelor of Science in Data Science Sep 2020 - Jun 2024

- Academic: Cumulative GPA 88/100

- Relevant Courses: Probability Theory; Data Mining; Machine Learning; Data Visualization PROFESSIONAL EXPERIENCE

KuaiShou Technology (HKG: 1024) Beijing, China

Assistant Data Scientist Jun - Jul 2023

- Analyzed behavioral patterns of 60,000+ users using Logistic Regression, Random Forest and XGBoost, uncovering a 12% engagement fluctuation. Insights drove a 2-week optimization project, improving regional content strategies

- Built KNN models in Python to predict user engagement and churn, applying hypothesis testing to validate proactive intervention strategies that reduce churn risk

- Identified seasonal trends through Time Series analysis, validating a 30% holiday surge in video views. Findings supported 3 initiatives, increasing user engagement by 8%

- Processed 500,000+ rows of data weekly using SQL and Excel, creating 10+ weekly Tableau dashboards with time-series analysis to monitor trends, improving decision-making efficiency by 10%.

- Evaluated campaign performance with Linear Regression and ANOVA, uncovering trends that boosted engagement by 18% and transactions by 11%, contributing to a 95% Q2 payment OKR achievement. Qihoo 360 Technology (SHA: 601360) Beijing, China

Intern Data Engineer Jan - Mar 2023

- Developed and optimized ETL pipelines using Apache Spark to preprocess and transform large datasets, creating 100+ PC user profile tags. Applied clustering and classification models to improve targeted recommendations by 10%

- Assisted real time A/B testing deployment with TB-scale test data preparation, structured experimental design, feature design and defining key metrics (user satisfaction and engagement). Post-launch analysis revealed a 15% increase in satisfaction

- Utilized advanced SQL techniques (Lateral View Explode, CASE, Over clause) to design and optimize 30+ dashboard metrics, prioritizing 10 key metrics. Enhanced visualization and reporting efficiency by 12% Alibaba Group (HKG: 9988) Beijing, China

PTA Data Analyst Jan - Mar 2022

- Led data cleaning and modeling efforts using Python, processing 100,000+ rows of order data to identify key performance indicators such as customer lifetime value and purchase frequency

- Developed RFM and Life Cycle Models, leading to a 15% increase in user retention for the E-commerce Strategy Department

- Utilized Excel VBA for Financial Ratio Analysis and Cash Flow Modeling, producing 5 investment research reports that identified 20% cost-saving opportunities and supported 3 strategic investment decisions PROJECT EXPERIENCE

Kaggle Competition, Multimodal Single-Cell Integration Beijing, China Solo Researcher Aug. 2023 - Dec. 2023

- Ranked 34th out of 1220 teams worldwide, Top 3% (Won the Silver Medal)

- Developed deep learning models using Python and PyTorch, predicting RNA and protein levels in two steps: a) DNA RNA, b) RNA protein. Achieved a Pearson correlation coefficient of 0.85 for RNA prediction and 0.92 for protein prediction.

- Pre-processed raw data by library-size normalization and TF-IDF, applied truncated SVD for dimensionality reduction, and implemented feature selection by excluding low-variance features, leading to a 10% improvement in model accuracy

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