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About
I believe every data point "represents a customer". I believe in putting myself in the end user's shoes for designing a data product. My focus is on the entire lifecycle: from data pipelines and model training to deployment, monitoring, and the human decisions they support. Also, I'm a huge sports analytics enthusiast/addict. Whichever way you want to look at it.
I'm drawn to the intersection of engineering rigor and product thinking, where the goal isn't just technical correctness but real impact on users and business outcomes.
Education
UCLA
B.S. Statistics & Data Science + B.A. Economics
Graduated 2025
London School of Economics
Machine Learning in Practice – Summer School
Grade: A
Skills
Languages & Tools
Python
R
SQL
Git
FastAPI
Streamlit
Docker
Tableau
Excel
Platforms & Databases
GCP
AWS
Azure
PostgreSQL
BigQuery
Snowflake
MySQL
ML & Data Science
scikit-learn
Feature Engineering
Model Evaluation
RAG / Embeddings
FAISS
Forecasting
Time Series
Clustering
Classification
NLP
Data Engineering
ETL / ELT
Data Modeling
Airflow Concepts
CI/CD
Logging & Monitoring
Performance Tuning
Model Versioning
Analytics & BI
KPI Design
Cohort Analysis
A/B Testing Basics
Data Storytelling
Product & Communication
Product Thinking
Prompt Engineering
UX for Data
PRDs & Specs
Stakeholder Alignment
Writing & Narrative
Resume
Open to roles in data engineering, ML engineering, and AI systems.