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Yue LiuPHONE NUMBER AVAILABLE EMAIL AVAILABLE LINKEDIN LINK AVAILABLE Street Address  Frank E Rodgers Blvd S, Harrison, NJ EDUCATIONUniversity of Chicago, Chicago, IL Sept 2021  Dec 2022 Master of Science in Applied Data Science GPA:3.89 University of Rochester, Rochester, NY Sept 2016  May 2020 Bachelor of Science in Applied Mathematics, Business: Finance GPA:3.67 SKILLS & QUALIFICATIONS Statistics and Machine learning: Linear Regression, Probability, Hypothesis Testing, SVM, Random Forest, XGBoost, AdaBoost; Deep learning (TensorFlow, Keras); NLP Coding and software: Python (Pandas, NumPy, scikit-learn, Seaborn); Excel; Hive, MySQL; Tableau; Hadoop; Google cloud platform, Bigqeury; Spark & Pyspark; MongoDB, Neo4j PROFESSIONAL EXPERIENCEReady Warehousing & Logistics (3PL) Oct 2023- May 2024 Data Analyst Python, SQL, Tableau Secaucus, NJ Leveraged Python to transform data and conduct a comprehensive analysis of storage capacities, turnover rate, demand variation, and labor cost with visualization including Pareto & ABC Analysis; presented strategic recommendations for charge adjustment and resource allocation to stakeholders, resulting in a successful 10% increase in profit Utilized Tableau to create daily summarization dashboards on operational performance, facilitating close monitoring of staff supply and demand for operation headcount optimization Designed and implemented a predictive inventory control system incorporating machine learning models, accounting for variability in arrival times of ocean freight shipments and historical outbound orders to optimize SKU-level inventory, mitigating stockouts and overstocking for enhanced customer satisfaction and turnover rate Automized data entry process leveraging Python (Tesseract, Regex) to extract order details of over 30 SKUs from image-based PDFs, containing cost estimation and calculated routing; seamlessly integrated the solution into the Warehouse Management System (WMS), yielding a notable 11% reduction in labor costs Maintained SQL database and served as analytical support to perform ad-hoc queries with MySQL to address client inquiries regarding charges, orders, and storage inventoryATZ Trading Inc July 2023- Oct 2023Data Analyst, Intern Python, Excel New York, NY Leveraged Python to analyze customer purchasing behavior, identified important churned customers, generated the customer contact list, and coordinated with the sales team for customized promotion, improving customer retention by 16% Developed key performance indicators (KPIs) to monitor and report fetching accuracy, frequency of errors, and impact on delivery performance; automated summarization order quantity for each delivery route for the verification process, reducing error fetching rate by 80% Utilized market basket analysis(Python) to identify trending sales, slow-selling products, and bundle sale items, adjusting promotional strategies to optimize in-app and poster promotions, resulting in a 9% increase in average order value and conversion rate among Japanese restaurant customers in New York and New Jersey V V Renter Inc March 2023  July 2023Data Scientist, Intern MySQL, Tableau Remote (Alhambra, CA) Located important factors that influence the number of rentals by building ML models SVM, random forest, and AdaBoost with feature importance(Python); suggested strategies to increase rentals including rental price, discount, different pickup location charges, etc; recommended 5 car models with rental price for upcoming business expansion with breakeven points Flattened a nested JSON file, cleaned and normalized car rental data into 5 tables from multiple sources; updated data and performed ad-hoc querying with MySQL to monitor monthly rental rates, price changes, and promotions IRI Worldwide, April 2022  Dec 2022Capstone Project Researcher Python Chicago, IL Led a group of 4 to research Synthetic Data Generation models and used cases, customizing statistical evaluation metrics such as boundary adherence and columns correlation, and developed and tested 4 Generative Adversarial Network models to opt for the Copula GAN model as the most promising with a statistical similarity score of 97% Reported to the R&D team monthly with progress, delivered a demo and a 30-page academic research paper, and showcased the final deck to both the R&D team and vice president to guide further development in addressing data privacy issues PROJECT EXPERIENCEYelp Recommendation System Big Data Project  PySpark and GCP January 2022  March 2022 Set up a Google Cloud Cluster environment and imported 11GB of nested JSON data into BigQuery; performed Explanatory Data Analysis for 8 tables on restaurant information (PySpark.sql, Seaborn) in Dataproc Developed NLP classification models on user reviews (Bert) to generate 7 clusters of restaurants, and further built ML models(Random Forest, Support Vector Machine, and AdaBoost) including those 7 clusters to recommend the top 10 restaurants to each user (PySpark ML), ultimately identifying the best model as Random Forest through Grid Search tuning