Supply Chain Machine Learning

Zhenhao Yan

517-***-**** *****@****.*** www.linkedin.com/in/zhenhao97

Education

University of Pittsburgh, Joseph M. Katz Graduate School of Business April 2022 Master of Science in Marketing Science + Business Analytics Pittsburgh, PA Michigan State University, Broad College of Business December 2019 Bachelor of Art in Hospitality Business East Lansing, MI Professional Experience

CorePower Magnetics May 2022-July 2022

Marketing Research Specialist Pittsburgh, PA

• Evaluated current electric vehicles market and predicted EV market, including forecasting sales and market share, in the next 5-10 years

• Assessed electric vehicles’ supply chain and CorePower Magnetics’ main competitors by analyzing the existing supply chain to identify main competitors

• Leveraged secondary research reports to find potential partner companies for CorePower Magnetics

• Developed promotion plan and strategies, such as attending expos and implementing traditional advertising methods, for CorePower Magnetics’ product

Mega Cat Labs/Mega Cat Studio June 2021-July 2021

Digital Marketing Internship Pittsburgh, PA

• Discovered current market of blockchain games and its users/player

• Pioneered gaming industry event and obtained potential speakers

• Boosted sales in Steam by click funnel, customer journey, personas, A/B testing strategies and Steam pages optimization

Pediatric Palliative Care Coalition (PPCC) June 2021-July 2021 Consultant, PPCC Mobile App Pittsburgh, PA

• Analyzed current healthcare apps market across different platforms, including android and IOS by referencing Top 5 Healthcare Apps as measured by downloads

• Proposed possible business/Financial models for PPCC’s future operation; referred to other NGO operation models to make recommendations

• Built a list of potential Grantmakers by researching similar NGOs where PPCC may meet donation requirements Graduate Projects

Business analysis: CarMax analytics Showcase October 2021

• Data Validation: Ensured input data’s correctness, meaningfulness, and security

• Evaluation: Tested data set to identify significant variables that may affect the company’s goal

• Interpretation: Analyzed current market and data set, composed feasible proposals for future operations Machine Learning & Forecasting: Preventing food deserts in United States January 2021

• Data Cleaning: Transformed data into readable input in Excel by Python

• Develop Indicator: Analyzed food desert data variance to perform a sample significance difference test in SPSS modeler

• Machine Learning: Applied linear and logistics regressions to establish model and predict best treatment scheme

Market Research: Heineken 0.0 September 2020

• Questionnaire Design: Established targeted questions to collect critical information, including consumer demographics, drinking habits, favorite beer brand, etc.

• Correlation Analysis: Determined significant variables that can potentially affect consumers’ beer brand selection and collected data sets by SPSS

• Reporting: Explained the significant relationship among interaction variables; presented results with appropriate interpretation

Data Analysis & Visualization: Adobe Analytics Challenge October 2020

• Data Visualization: Visualized and filtered required sales and history data from provided data set

• Data Analysis: Explored relationship between numerical and categorical data

• Prediction: Utilized existing data to analyze and forecast; created suggestions to increase future sales Skills

• Tools: Python, SQL, R, Tableau, IBM SPSS, and SPSS Modeler, Statgraphics, Microsoft Excel (Proficient in most functions: VLOOKUP, pivot table), Google Ads & Analytics

• Professional Skills: Data Mining, Database Management, Data Visualization, Statistical Modeling, Forecasting, Machine Learning, Project Management, A/B Test, Regressions

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