Supply Chain Digital Marketing

Ruimin (Rebecca) Ma

*** ******** ***, *** ****, NY 10025

+1-917-***-**** ******@********.*** https://www.linkedin.com/in/ruimin-ma-a49b6a1b1/ EDUCATION AND AWARDS

Columbia University, Columbia Business School & Columbia Engineering New York, NY Master of Science in Business Analytics GPA: 3.6/4.0 Exp Dec. 2024

• Relevant Courses: A/B Test, Market Analytics, Digital Marketing, Supply Chain, Data Visualization The Chinese University of Hong Kong, Shenzhen Shenzhen, CN Bachelor of Science in Statistics GPA: 3.8/4.0 (Rank 1/97), First Class Honor Sep. 2019 – Jun. 2023

• Relevant Courses: Machine Learning (NLP), Regression Analysis, Optimization, Time Series, Consumer Behavior SKILLS & OTHERS

• Analytics Skills: Feature Engineering, Database(MySQL, Spark), A/B Test, Cluster Analysis, Time Series Analysis

• Programming: Python, R, MATLAB, c/c++, SQL, JavaScript, CSS

• Frameworks: Spark, Sklearn, TensorFlow, PyTorch, XGBoost/Catboost, Pandas, NumPy, Scikit-Learn,

• Visualization: Matplotlib, Tableau, Power BI, Excel (Power Pivot, Power Query), Google Sheets PROFESSIONAL EXPERIENCE

Costo Time Series Analysis New York, NY

Data Science Intern Jun. 2024 – Current

• Utilized a structural VAE model to analyze price transmission from crude petroleum to plastics products

• Assessed the stationarity and seasonality of oil and plastics prices through visualization and analysis of the ACF and PACF, quantifying lagged relationships via cross-correlation between the two series

• Developed SARIMAX models in Python to forecast future plastic prices with a 3-month oil price lag as an exogenous variable, achieving an MSE of 0.039

TikTok Cluster Analysis Beijing, CN

Data Science Intern Jun. 2022 – Jan. 2023

• Conducted exploratory data analysis on 1M users with demographical variables and TikTok behavior features

• Developed a K-Means clustering algorithm in Python to segment and label above users into 10 groups

• Implemented logistic regression to estimate each user group's revenue potential with 89% accuracy

• Cross-validated the revenue data and analyzed risks with the local business team to target users Tencent Product Analysis Shenzhen, CN

AI Product Manager Intern May. 2021 – Oct. 2021

• Leveraged SQL queries to extract and analyze product usage data, identifying areas of downward revenue

• Collaborated with client teams to define technical dependencies and key metrics for 2 new features in PRD; worked with UX team to refine product interfaces in Figma.

• Prioritized engineering development roadmaps using WeCom and hosted daily meetings to ensure timely launch of new events, resulting in a 40% increase in user engagement and a 10% increase in subscription rates PROJECTS EXPERIENCE

Sentiment Analysis on IMBD Movie Comments Columbia Engineering New York, NY

• Developed web scraping scripts using Python and BeautifulSoup to extract 50k movie comments from IMBD

• Conducted feature extraction by executing PoS tagging, lemmatization with bag of words and TF-IDF

• Established a sentiment analysis system employing Random Forest, SVM and Logistic Regression models, achieving an 86% F1 score

A/B Test on Promotion Strategy Columbia Business School New York, NY

• Build dynamic and interactive sales dashboards using SQL and PowerBI, captured and reported on KPIs

• Applied chi-square and t-test to ensure effective randomization and unbiased results across users profile

• Stimulated A/B test on Google Analytics with sample size and over a one-week duration to assess different coupon strategies; revealed that 20% sales as most compelling with 32% ROI on young female users LEADERSHIP EXPERIENCE

Apartsa (https://www.linkedin.com/company/apartsa/) Shenzhen, CN Co-founder & Product Lead Oct. 2021 – May. 2023

• Product Development: Developed an on-campus information-sharing platform from 0-1, accumulating over 2k users and winning the China Internet Entrepreneurship Competition with 100k funding

• Team Operations: Orchestrated team resources and budgets, achieving a 20% surge in resource utilization efficiency and a 37% cut in operational costs through digitalized workflows

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