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Education

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Columbia University, New York, NY Dec. 2024

MS Computer and Information Science - Applied Analytics GPA 4.15/4.00

• Relevant Coursework: Data Modeling│Distributed Systems│Database Management│Anomaly Detection│Machine Learning

• Honor: Annual Dean’s Excellence Awards of Academic Leadership; Executive Member of Columbia Student Organization

University of Wisconsin - Madison, WI May 2023

BBA Wisconsin School of Business – Accounting GPA 3.7/4.00

Skills

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Python PostgreSQL Data Visualization R Language Exploratory Data Analysis

MongoDB API Design Statistical Inference BI Reporting Interactive Programmin

Metabase Research Design Machine Learning Apache Spark Regression Modeling

Experiences

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Business Analyst Intern at Shanghai Shenchi Industrial Co., Ltd., May 2023 – Sep. 2023

• Designed a dynamic financial KPI dashboard that helped identify cost-saving opportunities, led to a 15% reduction in operational costs and a 30% increase in decision-making efficiency.

• Conducted variance analysis using R language, pinpointed cost-saving opportunities totaling $100,000 and formulated strategic recommendations for profitability optimization.

• Applied Python to optimize logistics, analyzed age and mileage characteristics of trucks, informed business decisions, and boosted truck salvage value by 20%.

• Presented cost management strategies using Tableau, which resulted in a 25% increase in adoption of cost-saving measures.

Data Analyst Intern at Amazon.com, Inc. June 2022 – Sep. 2022

• Conducted market analysis using SWOT and Porter’s Five Forces to evaluate Amazon's competitive position, identified potential threats, and delivered strategic recommendations that informed leadership decisions.

• Designed a Tableau storyboard to visualize subscription trends and seasonal patterns, optimized marketing strategies, and identified 10% more growth opportunities in targeted demographics.

• Developed predictive models in R, spearheaded data cleaning, feature engineering, and modeling, enhanced data quality by 30%, and improved model accuracy by 20%.

• Produced actionable business intelligence by analyzing complex datasets, identified popular content genres, and informed investment strategies for original content, led to strategic expansion into untapped markets and an estimated ROI of 10%.

Projects

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Capstone: North America Logistics Optimization – Project Manager Sep. 2024 – Dec. 2024

CNH Industrial

• Developed a customized logistics optimization algorithm from scratch using Python, reduced logistics costs by over $400,000 through the integration of inland and ocean transport cost optimization.

• Designed a user-friendly API interface with HTML scripts for non-technical employees to interact with the algorithm, reduced manual input errors to 0%, and incorporated early warning alerts to further minimize disruptions.

• Enhanced the batch order processing algorithm to address business challenges, improved logistics efficiency and customer satisfaction by balancing costs with accurate delivery predictions and backup alternatives, and optimized the algorithm to deliver business recommendations in seconds, reduced shipment planning time by 80%.

Machine Learning Neural Networks Project – Individual Contributor May. 2024 – Aug. 2024

• Algorithm Development: Designed and trained neural networks with advanced techniques, including BatchNorm, to enhance performance and robustness. Developed a model capable of effective sequence learning and superior accuracy.

• Optimization: Employed PyTorch LSTM to further refine the algorithms. Achieved over 98% accuracy with a 30% improvement.

• N-gram and MLP: Implemented N-gram models and Multi-Layer Perceptron for complex data patterns. Developed a company name generation model with nearly a million parameters, significantly boosting the accuracy and reliability of predictions.

Airbnb Customer Satisfaction Analysis – Project Manager Jan. 2024 – Apr. 2024

• Clustering Analysis: Integrated PCA analysis, analyzed clusters based on rating metrics and neighborhood distribution.

• Inferential Statistics: Applied quantitative analysis indicating features influence customer satisfaction, employed inferential statistics to validate findings.

• GBM Regression: Applied predictive modeling and feature importance analysis to identify key predictors impacting satisfaction.

• Text Mining: Analyzed customer sentiments and distribution patterns, providing nuanced insights into trends and preferences.

Relational Database Design – Project Manager Jan. 2024 – Apr. 2024

• ETL: Spearheaded data collection, normalization, ER-Diagram design, and loading into the PostgreSQL database.

• API Development: Led the creation of an API interface integrated PostgreSQL backend, enhancing information management and implementing stringent security protocols, resulting in a 50% reduction in data manipulation time.

• Metabase: Developed an interactive dashboard, featuring pre-defined queries for streamlined data analysis and decision-making, resulting in a 40% improvement in executive reporting efficiency.

Leadership

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Program Representative at Columbia University Feb. 2024 – Feb. 2025

• Exemplary student leader; Faculty collaboration; Program improvement; Student feedback integration

President, Applied Analytics Club at Columbia University Mar. 2024 – Feb. 2025

• Led 6 teams of 30 students to organize 20+ events per semester, attracted 1000+ attendees, achieved a 98% satisfaction rate

JUNJIE WANG

New York, NY │ 551-229-2307 │ jason011207@gmail.com │ LinkedIn │ Personal Website