Data Scientist at Squared X - Remote

Developed and deployed 900+ SKU-level forecasting models trained in parallel, enabling scalable demand forecasting across large retail assortments. Designed automated retraining pipelines with drift monitoring to maintain model performance across dynamic retail environments. Implemented PACF-based lag selection to identify statistically significant autoregressive terms per SKU, enabling data-driven feature construction for demand forecasting. Contributed to promotion baseline estimation and pull-forward effect approximation, helping retail clients better isolate true promotions. Developed a multi-class product classification model for fashion retail, accurately categorizing clothing items across 75+ classes. Technologies: PySpark, MLflow, Pandas, FFT-based features, Databricks.

Data Scientist at Beauty Quick - Remote

Enhanced search engine v2.0 with improved precision and intelligent product recommendations for out-of-stock items, reducing customer bounce rates. Designed and refined product taxonomy for fragrance and makeup categories, improving product discoverability and search structure. Collaborated closely with engineering and product teams to deploy AI features into production environments.

Data Scientist at Beauty Quick - Remote

Data Scientist Intern: Performed iterative testing, debugging, and prompt optimization to improve chatbot response quality and user interaction reliability. Built and integrated an LLM-powered chatbot recommender using LangChain and FAISS for semantic search and conversational recommendations.