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Click here or scroll down to respond to this candidateCandidate's Name
New York, NY PHONE NUMBER AVAILABLE EMAIL AVAILABLE LINKEDIN LINK AVAILABLE EDUCATIONUniversity of Southern California Los Angeles, CA May Street Address Master of Science in Communication Data Science GPA: 3.92/4.0 Syracuse University Syracuse, NY December 2020Bachelor of Science (Summa Cum Laude) in Economics, double major in Advertising GPA: 3.8/4.0 (Deans List 2017-2020) SKILLS Data Analytics: A/B Testing, Casual Inference, Tableau, PowerBI, QlikSense, SAS, Google Analytics, Excel (VBA) Machine Learning: Python (Scikit-Learn, Pandas, NumPy), Predictive Modeling, Hypotheses Testing, Regression Analysis Database Processing: SQL Server, Microsoft Access, AWS S3, Snowflake Data Engineering: Spark, Hadoop, Hive, MapReduce PROFESSIONAL EXPERIENCECredit Risk Data Analyst Consultant Bank of China New York New York, NY Jun. 2023- Present Developed an ETL pipeline leveraging SQL to integrate diverse credit-related datasets, resulting in a 50% reduction in quarterly CECL calculations. Enhanced the robustness and scalability of the credit management department Revolutionize data processing workflow by extracting financial information using Python (PyPDF2, Pytesseract); Achieved a remarkable 70% reduction in data processing time while enriching text data for portfolio analysis Designed a comprehensive data governance solution by constructing a risk rating tracking database in Microsoft Access with VBA. Reduced risk rating approval response times to under one week, mitigating credit loss risks and facilitating seamless synchronization with the head office Developed a loan monitoring system within QlikSense dashboard, enabling the identification of Key Risk Indicators (KRI) on a weekly basis. Drastically reduced communication latency across multiple departments, empowering senior management to make informed, real-time decisions Established NYC Real Estate submarket sub-limit based on loan profiles using Excel (PivotTable, VLOOKUP, VBA). Facilitated the remediation of MRA and led to a reduction in the banks overall risk profile Monetization Product Analyst Intern TikTok Shanghai, China Jan. 2021- June 2021 Conducted A/B testing on TikTok's advertising product, comparing sticker-enabled and non-sticker groups. Utilized Python for data analysis, highlighting higher engagement and video uploads with stickers, enhancing client ROI and guiding future product recommendations Analyzed audience engagement metrics for TikTok advertising products using Python (Pandas, NumPy, Matplotlib) and Excel(PivotTable), resulting in a 65M growth and informing long-term monetization product strategies Utilized media mix modeling with time series regression to optimize budget allocation across various media types, leading to a 21% increase in ROI of client, while retaining key account customers Conducted attribution analysis to evaluate diverse advertising elements including influencer collaborations, stickers, and e- commerce links in Python. Optimized the budget allocation and increased the engagement rate of ad products Built a monetization advertising product stock map using Tableau, facilitating communication between product and sales teams and contributing to the sales of less popular ad products Account Executive Intern DDB Worldwide China Group Shanghai, China May 2019 - July 2019 Performed the market research regarding to the home appliance industry from the marketing campaign channel allocation perspectives by using PEST and SWOT framework Forecasted the ROI by constructing the media budget allocation plan using Excel Created and presented the media impression competitor reports and creative briefs for stakeholders with key market trends and opportunities, it was well-received by themPROJECTSRestaurant Business Analysis for Chinese Cuisine (5-person team) Los Angeles, CA Mar. 2023 May 2023 Developed a web crawler to retrieve 20GB+ restaurant profiles on Yelp, including customer reviews and ratings with APIs Identified 10+ important features related to customer rating score in linear regression and XGBoost model; Improved prediction performance by 0.12 via with 5-fold cross-validation and GridSearchCV Led the team of 5 to visualize how multiple factors interactively affects customer ratings for restaurant owners in Tableau Movie Recommender System Los Angeles, CA July 2022 Aug. 2022 Engineered 100k movie data from database and extracted 15+ usable features including movie type, country, length etc. Converted movie descriptions into word/sentence embeddings and conducted dimension reduction via PCA Created the movie recommendation system by using collaborative filtering recommender, content-based recommender and hybrid models to recommend movies based on the similarity Created and presented a demo video to present the project to non-tech audiences and other stakeholders |
