Vandemberg Monteiro
Data Scientist experienced in designing and deploying data-driven solutions across finance and healthcare.
Skilled at translating complex analytics into actionable insights and supporting effective decision-making with robust, impactful solutions.
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Selected Projects in Data Science and Machine Learning
Grounded conversational Amazon items recommender system with explicit retrieval and reranking
In this project, I built an end-to-end conversational recommendation pipeline that turns natural-language user requests into structured preferences, retrieves plausible candidates, grounds them with product metadata and review evidence, reranks them with explicit signals, and returns explainable recommendations. The goal is to add conversational flexibility without handing the full decision process to an opaque LLM.
The project emphasizes controllability and inspection over black-box generation. Instead of letting a language model decide everything, the system keeps retrieval, grounding, and ranking behavior explicit and testable, while using natural language as an interface layer for preference interpretation and response generation. It also includes evaluation of retrieval, parsing, reranking, and explanation quality, along with a simple CLI chat interface for interactive use.
End-to-end credit risk modeling with decision and policy analysis
In this project, I develop an end-to-end credit risk modeling pipeline, focusing not only on predictive performance but also on decision-making, model stability, and risk policy evaluation.
The work includes feature engineering and preprocessing, gradient boosting models for risk ranking, model interpretability with SHAP, stability and behavioral analysis over time, and the translation of scores into approval policies and risk-return trade-offs.
The project also explores deployment considerations and causal analysis to better understand drivers of default beyond correlation.
