Digital Marketing Data Analytics

LUYI TONG

*****@**.*** 206-***-**** www.linkedin.com/in/luyitong

EDUCATION

University of Washington Seattle, United States

Master of Science, Biostatistics Sept, 2024 - 2026 (Expected) McGill University Montreal, Canada

Bachelor of Arts, Honours Probability and Statistics Sept, 2020 - June, 2024 Related courses: Analysis, Probability, Statistics, Regression and ANOVA GPA: 3.72/4.00

Minor: Economics

EXPERIENCE

Digital Marketing and Data Analytics Intern

Ningbo Chunqiu Guantu Culture and Media Co., Ltd May, 2022 − Sept, 2022 Zhejiang, China

• Developed a centralized data warehouse to consolidate marketing data from 20+ cross-channel API logs (impressions, clicks, conversions) using Hive, improving data accessibility by 40% and enabling performance reporting.

• Engineered ETL pipelines to automate data extraction and transformation, integrating user interaction data into a centralized data lake. Reduced manual data processing time by 60%.

• Designed and implemented a Shapley Value attribution model to evaluate marketing channel effectiveness, leveraging PySpark to calculate contribution metrics, increasing budget allocation accuracy by 20%.

• Created RFM analysis dashboards to monitor customer engagement and purchasing behavior, using SQL and Tableau to provide real-time insights. Enabled targeted campaign strategies that boosted repeat purchase rates by 15%.

• Implemented real-time data pipelines using Flink for coupon redemption monitoring and fraud detection. Detected and blocked 15% of abnormal traffic, enhancing data integrity and system performance.

• Developed Tableau dashboards to visualize KPIs, including CTR, ROI, and revenue trends, facilitating data-driven strategy adjustments for the marketing team.

PROJECT WORK

Product Value Tiering Framework

• Developed a 3D value metrics system using Python to classify products based on CTR, cart-add rate, and cross-purchase frequency. Applied K-means clustering to segment products into strategic tiers, enabling targeted resource allocation.

• Built data integration pipelines to merge product performance data with inventory metrics from SQL databases, ensuring the accuracy of classification logic. Enhanced data reliability by 20% with automated validation.

• Engineered a text analytics pipeline using TF-IDF and Word2Vec to process 12 million daily search queries, identifying emerging product trends (e.g., smart pet tech). Built Tableau heatmaps to correlate price elasticity (89-159 CNY) with trending categories, streamlining inventory forecasting for 428 candidate SKUs with stock levels over 3,000 units.

• Implemented a linear programming model using Python PuLP to optimize the merchandising mix. Generated Pareto frontier solutions for resource-constrained environments, resulting in a 20% increase in merchandising efficiency.

• Automated real-time data extraction from multiple sources using ETL pipelines, reducing manual data processing by 60% and maintaining 99% data accuracy.

Multi-Channel ROI Modeling and Opportunity Identification

• Built data pipelines with PySpark and SQL to map user journeys across channels (e.g., in-feed ads, KOL), using time-decay attribution to identify high-impact combinations like KOL-driven discovery + retargeting.

• Developed GMV prediction models (Python) to correlate ad spend with user LTV, visualizing cost efficiency (CPM vs. user quality) via Tableau, identifying low-retention channels.

• Profiled channel performance (click depth, conversion latency) with PySpark, detecting ROI anomalies during competitive campaigns. Improved campaign accuracy by 25% through time-series analysis.

• Modeled channel elasticity with Scikit-learn to optimize budget allocation, validated through A/B testing, improving budget utilization by 15%.

CORE SKILLS

• Data Warehousing & ETL: Building and maintaining data pipelines, integrating data from multiple sources

• Data Modeling & Transformation: Designing data models, data cleaning, and preprocessing

• BI Reporting & Visualization: Developing interactive dashboards and reports using Tableau and SQL

• Data Integration & Automation: Implementing data extraction, transformation, and loading (ETL) workflows

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