Jun 2022 – Mar 2023 · 9 mos

• Partnered with Product-Led Growth Team, including product managers, engineers, and designers, to optimize the product and customer journey in confluent.cloud and drive key growth metrics, throughout the entire user funnel including acquisition, activation, engagement & retention, and revenue
• Designed and conducted A/B tests for new feature launches and evaluated experiment results by conducting user segmentation. Initiated and recommended personalized onboarding paths, leading to a 10% increase in onboarding activation rates for unfamiliar users
• Conducted deep-dive analyses including UI funnel analysis and user engagement analysis to uncover user behavior patterns and identify opportunities for in-product improvements by mining UI data and identifying key actions, resulting in a 5% reduction in churn rate
• Built and maintained end-to-end data pipelines and Tableau dashboards to monitor key performance metrics, and provided timely insights into metric movements assisting decision-making by the executive team
• Presented findings and actionable insights to senior management and cross-functional teams to help inform product strategies and contribute to the overall success of the Product-Led Growth motion

Jun 2020 – Jun 2022 · 2 yrs · New York City Metropolitan Area

• Project: YourDoctors — a patient and claim management system for healthcare providers
• Led and developed H2O Random Forest model using Python by formalizing and training 500,000 history claim records data to prevent denial and predict the claim payment from insurance companies
• Identified key metrics and measure KPIs, designed experiments to evaluate model performance and draw business insights, increased average reimbursement by 5%, and decreased claim denial rate by 3%
• Collaborated with engineers, data scientists, and product managers to deploy machine learning models into production on AWS, maintained and aligned data products regularly
• Project: SOMA — a remote patient monitoring wearable device connecting patients with doctors
• Prototyped a 3-layer LSTM RNN model to monitor sleep and classify 4-phase sleep stages
• Optimized model performance through careful and strategic hyperparameter tuning and feature engineering, which improved the model to surpass the baseline model performance by 6%
• Extracted, cleaned, and wrangled sleep data of 2,237 participants from National Sleep Research Resource (NSRR) including 1.5 million minutes signals (400GB) with sleep stage labels using SQL
• Explored and compared 30 cutting-edge journal articles about sleep stage classification using machine learning and neural networks and built models based on these research papers to find the optimal solution

Mar 2019 – Jun 2020 · 1 yr 3 mos · New York City Metropolitan Area

• Designed experiments and implemented A/B testing for email campaigns, increased click-through rate by 5%
• Analyzed user conversion funnel and customer behavior, defined metrics and user segmentation to optimize promotion strategy and increase engagement, and enhanced conversion rate by 3%
• Executed marketing and Ad data analytics to support decision making, and delivered data visualization panels and analytics reports to present insights to technical and non-technical stakeholders

Sep 2017 – May 2018 · 8 mos · Greater New York City Area

• Presented workshop lectures to 50 students on getting started with SQL and Oracle
• Graded assignments about SQL queries, ER diagram, and database design every week