Here’s a quick look at my background —
how I’ve been learning, building, and growing as a product-minded business analyst.
Education
Columbia University
M.A. in Statistics · Financial Risk & Modeling Track
Fall 2024 - Winter 2025
McGill University
B.A. Honors in Probability & Statistics · Minor in Economics
Fall 2019 - Spring 2023
Work Experience
Product Strategy Intern
Alibaba Group · Business Intelligence Center
Summer 2025
Evaluated feasibility and adoption of in-vehicle AI agents and turned research into pilot roadmap recommendations.
Built an AI commercialization framework connecting inference cost, pricing, and downstream value chain — later used in strategic planning.
Prototyped a BI news agent (Python + APIs) that automated daily updates and cut manual monitoring time by 50 %.
Product Launch Intern
KOIN · AI Fintech Startup
Spring 2023 - Winter 2023
Product:
Benchmarked AI-powered investment platforms and synthesized a strategic matrix to define MVP scope and identify high-impact product hooks around real-time, explainable stock insights.
Co-designed LLM prompts with engineers for financial insights extraction, testing chain-of-thought reasoning and tone alignment to improve factual accuracy and domain reliability.
Collaborated with the UX designer to evaluate onboarding strategies (e.g. agent-style Q&A vs traditional forms), contributing to decisions that improved early user engagement and feature discoverability.
Helped articulate Koin’s value proposition in the AI investment space by drafting pitch decks and demo narratives. Structured product storytelling to effectively communicate differentiators to investors and partners.
Programming:
Involved in the initiative to fine-tune ChatGPT. Collaborated with cross-functional teams to integrate the fine-tuned model into existing systems, improving user interaction and satisfaction.
Developed an algorithm for recommending follow-up questions based on relevance to users' previous queries, enhancing user engagement and platform intuitiveness.
Integrated a wide range of APIs to obtain real-time press reports and conducted sentiment analysis, supplying the chatbot with up-to-date data sources.
Product Operation Intern
Tencent · PCG Platform & Content Group
Summer 2021
Reviewed search recommendation queries for 100M+ users, helping refine filtering rules and standardize audit workflows for consistency.
Extracted high-frequency user feedback from multiple platforms. Categorized issues using a custom tagging framework and authored reports that informed multiple rounds of bad-case strategy improvements, boosting efficiency by ~20%.
Conducted structured data operations using SQL and Python to support product decision-making, including issue classification and trend analysis.
Analyzed A/B test results to evaluate strategy changes and collaborated cross-functionally to align audit logic with feedback, optimizing closed-loop handling.
Research Experience
McGill University - Thesis (Causal Inference & Structural Modeling)
Supervised by Prof. Archer Yang & Dr. Marc-André Legault, with interest in Causal Inference Analysis in Biological Information.
Delved into advanced statistical methods, including deep IV and quantile IV, studying their implications and applications in biological data analysis.Worked on exploring the integration of deep learning techniques with instrumental variable quantile regression mode, aiming to innovate and enhance predictive modeling in biological datasets.
City University of Hong Kong - RA (NLP & Predictive Modeling)
Research Assistant supervised by Prof. Linyan Li, with interest in NLP pipeline to structure medical records and boost model accuracy on patient-risk prediction.
Initiated a forward-thinking research proposal centered on the analysis of unstructured text data within EHR, focusing on the application of cutting-edge neural and deep-learning techniques, particularly exploring the capabilities of LLM models for data summarization and prediction. Employed the MIMIC-IV datasets as the primary data reference, cleaned the data with normalization and standardization, aligning them with ICD-9 and ICD-10 coding systems.