• Designed a climate tech information database from scratch, collaborating with software engineers to enhance visibility and provide strategic insights to the C-suite on website design support• Led 8 teammates to establish data requirements and validate 100k+ data points scraped from 93 sources in Python; preprocessed and backfilled 20k+ missing values to enhance database completeness, supporting the daily work of 4 departments that consume the database• Developed a sector classification model to assign industry sectors to 3,000+ companies and podcasts, achieving over 70% accuracy• Conducted text mining for keyword analysis from company descriptions, visualized industry demand forecasting using a Power BI dashboard, and guided data-driven decisions on prioritizing website development fields, resulting in a 3% revenue increase• Facilitated knowledge transfer by training the marketing team on showcasing drill-down dashboard features in Power BI, empowering them to independently analyze data for self-sufficient decision-making, resulting in a 20% reduction in time spent on the ad-hoc requirement

• Conducted funnel analysis to map the user journey and optimize social media channels through targeted content, identified a profitable customer group, reducing the bounce rate by 5%• Executed A/B testing with Google Analytics to determine the more effective copywriting on the ordering webpage, aligning with product managers on sample size and success metrics, resulting in a 12% increase in click-through rate and an 8% increase in conversion rate• Created ARIMA time series models in R to forecast seasonal inventory needs with 83% accuracy, automated reports on sales predictions, which reduced stockouts by 8%• Developed a SQL-based ETL pipeline to process 30k+ web tracking data points, incorporating data slicing for detailed seasonal and regional analysis• Built KPI dashboards in Power BI to visualize analysis results, enabling a deep dive into sales trends, customer behavior, and operational issues, increasing reporting efficiency by 30%

- Visualized customer profiles and sales trends in Chinese snack industry in Tableau dashboard; reduced turnaround time for ad-hoc analysis by 8%- Analyzed top 10 snack companies’ revenue trend and cost drivers by analyzing financial statements, DCF models, economic indicators and revenue/cost breakdowns to track profitability and solvency- Determined product priorities by investigating key drivers for online best sellers with highest repurchases on quarterly basis; reported marketing strategies to 200+ stakeholders- Initiated surveys for new snack flavors, collected responses and performed gap analysis in Excel Macro; identified customer preference and new opportunities

- Implemented a new recommendation system based on customer preferences through historical data in Excel to boost food sales, increased 15% monthly restaurant profits - Imporoved service quality by designing customer feedbacks survey and extracting keywords from reviews on social media, increased 50% positive customer feedbacks