Yangfeng Shi

• Implemented App Store Optimization (ASO) strategies to improve game visibility and user acquisition by researching high-traffic keywords and optimizing app store listings. Tools used included Google Keyword Planner, Ahrefs, and App Store Connect. These optimizations contributed to a 15% increase in organic downloads over a 3-month period • Improved ARPU by 10% by analyzing player behavior and in-game item data at the player cohort level in SQL • Increased player retention rate by 5% and total paying users by 10% in a month by performing in-depth funnel analysis, attribution analysis, and identifying 3 stages with the most severe player churn rate • Optimized player experience by monitoring 10+ KPIs, identifying and addressing issues for 50K+ users • Led 5 user operation specialists and collaborated with the game development team, solved 60% of problem users, and fixed 2 systematic issues • Increased ROI by 80% by evaluating the performance of 30+ marketing campaigns and further optimizing digital marketing strategies • Employed a K-means clustering model in Python to stratify 200K+ players based on in-game items, progression, retention time, payments, and active level • Created and managed 20+ automated and interactive dashboards in Tableau to monitor and track key metrics and further improved the efficiency of identifying player anomalies and monitoring resolution

● Implemented ELT procedures and established a data warehouse using Google BigQuery, to store diverse data, including marketing campaigns, marketing, customer, and Google Analytics data. Developed intricate SQL queries to create ad-hoc reports ● Produced employment and job openings research reports for different industries, including market overview, current trends, market size, segment performance, etc., with Tableau and Excel ● Web scraped and investigated review data from variate review platforms using Octoparse and word cloud analysis ● Analyzed competitive landscape by utilizing data from different data sources and drafting SWOT analysis and competitor analysis to assist management in the investor presentation ● Identified potential customers using customer segmentation analysis and predictive analysis with Python • Enhanced website SEO through content and technical optimizations by conducting keyword research, improving on-page elements, and implementing structured data markup. This resulted in a 20% increase in organic search traffic, while also reducing bounce rate by 10%, using tools such as SEMrush and Google Search Console ● Performed Google Ads marketing channel analysis on impression, click-through rate, and conversion rate to analyze the current return for different media. Run the A/B test for the marketing budget allocation on each campaign and the distribution for different media, resulting in customers increased by 210% with an ROI of 3.2 ● Utilized A/B testing and statistical tests helping the web design team to develop and improve the website ● Presented insights to the software design team to upgrade software’s features following SDLC

● Co-worked with IT teams and followed Agile Project Management Framework to review business requirements, design prototyping, develop, and test new application features to ensure functionalities are aligned with initial business objectives ● Participated in three projects and generated timelines for project planning phases using Jira ● Created workflow and built automated data pipelines and ETL with AWS Redshift, Python, SQL, Alteryx, and SSIS to process daily electricity usage data of 220k+ households ● Developed standard data quality routines to clean the source data as well as keep track of data quality matrixes ● Collaborated with 20+ internal stakeholders to conduct a data migration project from DB2 to SAP HANA Platform, increasing the speed of data aggregation by 34 times faster ● Discussed with the IT team to identify different success matrixes for the electricity bill payment website and performed A/B testing to optimize the payment process ● Applied time series analysis method to analyze the electricity usage trend. Predicted weekly usage and reported the high forecasting level weeks and months to ensure a high service level ● Reviewed and troubleshot complex SQL queries for 20+ Utility & Gas related reports, including Accounts Receivable Aging Report, No Standard Meter (NSM), Reduced Rate 175 and Switch Hold Report, etc. ● Developed & designed monthly Disconnect for Non-Pay (DNP) report using Tableau for Revenue Protection Team Identified accounts and prevented revenue loss of 2+ million ● Developed and optimized dashboards, Ad-Hoc Reports, Sub Reports, Drill-Down, and Drill-Through Reports to support 5k+ users and enhance users’ experience with Tableau and Excel Pivot Table

● Capstone Project ● Conducted a SWOT analysis of the software, providing valuable insights into customer growth and enabling the team to identify key areas of improvement ● Collected and cleaned over 50M+ third-party data from multiple sources using Python, improving data quality and accuracy for analysis ● Utilized SQL queries and Excel to analyze and report on the collected data, identifying trends and patterns that informed strategic decision-making ● Developed automated Tableau dashboards that provided real-time insights into product performance, enabling the team to quickly identify areas for improvement and make data-driven decisions ● Presented findings and insights from the dashboards to the Director of Product, resulting in a 15% increase in monthly profit

● Built Database with PostgreSQL and PostGIS to store energy data, finical data, and geographical data ● Performed ETL Process with SSIS for modeling, analysis, and other groups’ use cases ● Collected and cleaned electricity usage data from 100 major cities in China, and collaborated with senior data scientists to design machine learning models with Python to predict the future electricity demand ● Conducted investment and revenue prediction analysis using Deep Neural Network with Python ● Cooperated with the marketing and research teams to create dashboards for solar panel site selection using Tableau and presented the insights to executive officers for approval. Designed and Built 30+ solar energy generation sites ● Designed and executed a Business Intelligence training program to promote greater adoption of the use cases and BI tools throughout the organization, increased reporting efficiency by 15%