Data Analyst · MS Applied Analytics · Columbia University

Kimberly
Huang

Translating complex data into growth decisions. Experienced in product funnel analysis, dashboard engineering, and AI-assisted analytics — across e-commerce, finance, and SaaS platforms.

Get in touch Resume LinkedIn ↗
40%
Reporting time cut at Temu
12%
Activation lift via funnel analysis
4.0
GPA · Columbia University
Kimberly Huang at Columbia University
01 — About

Data-driven by instinct,
strategic by training.

I'm a data analyst based in New York, currently pursuing my MS in Applied Analytics at Columbia University. I specialize in turning messy datasets into clear decisions — optimizing product funnels, building executive dashboards, and designing AI-assisted analytics systems.

My background spans e-commerce analytics at Temu, securities research at Shenwan Hongyuan and SDIC Securities, financial operations at Holt Green, and independent AI projects including a health intelligence platform. I'm bilingual in English and Chinese, and hold the ACCA certification.

I'm drawn to companies building at internet scale — where data quality directly shapes how millions of users experience a product.

Analytics & Query
SQLPythonRStudioSPSSA/B Testing
Visualization
Power BITableauLooker
Cloud & Data Infra
AWSBigQueryPostgreSQLMongoDBAWS IoT
AI & ML
Machine LearningGenerative AIData Engineering
Finance & Research
BloombergWind DBiFindACCA
02 — Education
Expected Dec 2026
Columbia University
MS in Applied Analytics · New York, USA
GPA 4.0 · Machine Learning · Data Engineering · Applied Generative AI · Cloud Computing
Jun 2024
University of Dundee
BSc in Applied Finance · Dundee, United Kingdom
Top 1% GPA · 2022–2024 Global Excellence Scholarship · ACCA Certified
03 — Experience
Jun 2024 – Jul 2025
Temu · Shenzhen
Data Analyst
Analyzed acquisition, activation, retention, and monetization funnels across 20+ regional markets to support GMV growth and product led growth strategy. Built executive Power BI dashboards used in leadership reviews. Automated data pipelines in Python and SQL — reducing manual reporting time by 40%. Led pricing experiment analysis that identified onboarding drop-offs and drove a 12% increase in activation rates.
SQLPythonPower BIFunnel AnalysisA/B TestingData Pipelines
Aug – Sep 2023
SDIC Securities · Beijing
Research Analyst Intern, Product Team
Collected and synthesized policy, industry, and company data by tracking daily news and drafting statistical reports for senior analysts. Compiled analytical reports on the New Beijing Stock Exchange and New Third Board using Wind database and company prospectuses. Supported primary research on hydrogen energy, electricity, and traditional energy sectors. Updated monthly microeconomics reports across pharmaceutical, healthcare, and financial industries.
Wind DBMarket ResearchEquity AnalysisStatistical Reports
Jun – Aug 2023
Holt Green Training · Manchester
Finance Analyst Intern
Analyzed accounts receivable and payable using SQL to support financial reporting and reconciliation. Assisted with financial close processes including balance sheet, income statement, and cash flow review. Conducted internal compliance reviews to strengthen financial control frameworks.
SQLFinancial ReportingReconciliationCompliance
Mar – Jun 2023
Shenwan Hongyuan Securities · Beijing
Market Research Analyst Intern
Conducted macro and industry analysis using Bloomberg and iFind, synthesizing macroeconomic trends and competitive dynamics. Evaluated business models and financial performance of listed companies, delivering structured investment insights and market commentary for senior researchers.
BloombergiFindInvestment ResearchSector Analysis
04 — Projects
01 · Feb – Apr 2026
Signal2Action
Agentic AI system converting fragmented external signals into structured analytics outputs and strategic recommendations. Integrates real time data feeds to support A/B experiment design and adaptive decision cycles. Outputs are framed in a decision oriented format for nontechnical stakeholders.
PythonAgentic AIA/B TestingData Pipelines
View on GitHub ↗
02 · Oct – Dec 2025
EventScope
B2B SaaS financial intelligence platform processing 65,000+ SEC filings. Built end to end data pipelines and models in Python, SQL, and PostgreSQL — reducing processing time by 60%. API driven dashboards translate complex financial signals into decision ready insights.
PythonSQLPostgreSQLMongoDBDashboards
View on GitHub ↗
03 · Sep – Nov 2025
VitaSense
Real-time behavioral health intelligence platform combining edge devices (M5Stack) and MQTT streaming to capture continuous activity data. Built a scalable AWS IoT pipeline with 5,000+ historical records for ML feature engineering. Deployed models to detect abnormal movement patterns with an interactive early risk dashboard.
AWS IoTMQTTMachine LearningPythonM5Stack
Founder & Product Lead
04 · Feb – Apr 2026
ZeroToViral
AI driven content growth platform analyzing viral patterns across social platforms. Built a data pipeline to collect and structure engagement data, identifying key drivers such as hooks, formats, and timing. Developed an LLM assisted pipeline to extract and categorize content features from unstructured data into actionable growth insights.
PythonLLM APIsWeb ScrapingData AnalysisProduct Analytics
View on GitHub ↗
05 — Contact

Let's work
together.

Open to internship and full-time opportunities in data analytics, product analytics, and growth. Based in New York — available Summer 2026.

huang0818hqj@outlook.com LinkedIn ↗