Emily Gong Email and Phone Number

• Simulate opinions updates in a mathematical network with the Deffuant–Weisbuch model using Python• Create concise visualizations with computational simulations to unveil how opinions change in a network

• Provide one-on-one consultations for topics like logistic regression, odds ratio, and debugging in Python and R • Expanded audience reach by 51% via developing and executing multi-platform, sustained social media campaigns

• Grew client base by 20% by completing outreach to 60+ companies and designing a value proposition pitch deck• Coordinated various job networking events, alumni panels, and company info sessions, attracting 300+ attendants

• Led spring recruitment by coordinating with 100+ applicants, designed social media posts using Figma, manage 4 social media platforms (46% traffic increase on Instagram), and communicate with prospective club members• Extracted & processed osu! (a rhythm game) data through MongoDB, collaborated with a team on AWS, and predicted when players tend to fail in games using XGBoost’s Random Forest machine learning model

• Formatted inflation data using Pandas that helped streamline prediction for each country within Alteryx• Built 3 Tableau dashboards using 2k rows of data on the Data Center industry, catering towards different stakeholders: country-level, regional, and the strategy team• Discovered and fixed incorrect YOY growth rate in 25% of the original graphs and reduced the number of graphs by 80% while achieving the same result

• Penetrated e-commerce and online payment segments in the US for a Singapore-based Y-Combinator startup• Fostered a contract between the largest Asia-inspired night market (250+ vendors) and the startup• Utilized Notion to create and track tasks, monitored performance with weekly check-ins and work sessions

• Collaborated within a project team to strategize UrbanTXT, an educational non-profit, to transition their curriculum online, facilitate market entry, build competitor partnerships, and prepare for trademark/licensing

• Process time series world-wide Twitter data from 2006 – 2020 for 50+ countries with Python (data ~10 GB for one country); group and aggregate data using Pandas with respect to different activity categories• Create data visualizations with Matplotlib and Seaborn, perform transformations, and analyze trends and connect Twitter user activities with historical events in corresponding time periods, such as Arab Spring

Work on rigorous video and data analysis and collaborate with a team on thematic analysis to create tools to support teachers and improve their teachings in the classroom