Jie Hou Headshot

Jie Hou

Data Scientist | Machine Learning Engineer

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About Me

I am an M.S. Data Science student at UC San Diego with a solid foundation in experimental data analysis from a Physical Sciences background. I specialize in translating ambiguous product questions into measurable KPIs and building robust modeling pipelines. My passion lies in extracting meaningful signals from noisy real-world data and empowering cross-functional teams with actionable, data-driven insights.

Core Competencies

Causal Inference A/B Testing Time-Series Analysis NLP (DistilBERT) Python (PyTorch, Pandas) SQL R Statistics KPI Design ETL Pipelines AWS

Selected Projects

Experimentation & Causal Impact Analysis

Designed and executed A/B tests to validate UI/UX workflows. Conducted power analysis and evaluated statistical significance, providing actionable rollout strategies based on true causal impact.

Time-Series Signal Modeling Framework

Engineered a modular pipeline to transform noisy, real-time behavioral signals into interpretable features. Designed a robust framework to optimize action thresholds under uncertainty using trend decomposition.

User Intent Retrieval & NLP Safety Modeling

Built an end-to-end NLP pipeline fine-tuning DistilBERT to address extreme class imbalance. Improved rare-event detection F1-Score to 0.84 and reduced false positives by 10% in simulated settings.

Experience & Education

2025 - 2027

M.S. in Data Science

University of California San Diego
2020 - 2023

Graduate Research Assistant

Georgia Institute of Technology

Conducted research on experimental data analysis.

2019 - 2020

Research Intern

National Institute of Standards and Technology (NIST)

Assisted with physical sciences research and data collection.

2015 - 2019

B.S. in Physics

Delaware State University