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Achievement: Pull Sharkx2Achievement: Pair ExtraordinaireAchievement: QuickdrawAchievement: YOLO

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SimretAbebe/README.md

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FinTech ML Engineer & Backend Developer | Credit Scoring, Fraud Detection & Financial NLP | Django • Python

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🏦 Featured Projects

🇪🇹 Ethiopian Bank Review Intelligence

Multilingual (English/Amharic/Afaan Oromo) risk intelligence system built from Ethiopian bank app reviews.

100% recall on high-risk reviews · SHAP explainability · multilingual NLP · live dashboard

💳 Credit Risk Probability Model

End-to-end credit risk model using alternative transaction data and RFM-based proxy variables.

Basel II-aligned interpretability · Docker · CI/CD pipeline

🕵️ Fraud Detection System

Fraud detection across e-commerce and credit card transactions using multiple machine learning models.

Caught & fixed a data leakage bug in cross-validation · SHAP-driven business recommendations

🤖 RAG FinTech Complaint Chatbot

RAG-powered chatbot turning raw financial complaint data into instant, evidence-backed insights.

LangChain · ChromaDB · Llama 3

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  1. Fintech-Review-Analytics Fintech-Review-Analytics Public

    NLP sentiment & thematic analysis of Ethiopian mobile banking app reviews (CBE, BOA, Dashen) using spaCy/transformers, with PostgreSQL storage

    Jupyter Notebook 2

  2. Fraud-detection-Model Fraud-detection-Model Public

    End-to-end fraud detection pipeline comparing LR, Random Forest, XGBoost & LightGBM, with SHAP explainability

    Jupyter Notebook 1

  3. Credit-Risk-Model Credit-Risk-Model Public

    End-to-end credit risk model with Basel II-aligned interpretability, RFM-based proxy variables, Docker deployment, and CI/CD pipeline.

    Jupyter Notebook

  4. RAG-FinTech-Complaint-Chatbot RAG-FinTech-Complaint-Chatbot Public

    RAG-powered chatbot that turns raw customer complaint data into instant, evidence-backed insights for FinTech product, support, and compliance teams. Built with LangChain, ChromaDB.

    Jupyter Notebook