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amandahtay/README.md

Hi, I'm Amanda šŸ‘‹

I build quantitative models and data systems for financial markets. Founder of crediqs — building Financial Risk Intelligence Platform .

Most of my work is hands-on: data pipelines, transformation workflows, and analytics infrastructure designed for scalability, reproducibility, and performance.

I focus on clean architecture, efficient processing, and production-ready systems that support quantitative research and financial decision-making.

Open to: early design partners in accounting/finance, angel investors interested in EU fintech infrastructure, and engineering collaborators


What I work on

  • šŸ¦ Building crediqs: Financial Risk Intelligence Platform
  • šŸ“¦ Quantitative Data Pipelines: Market data ingestion → feature engineering → model-ready datasets (options Greeks, volatility surfaces, microstructure features)
  • šŸ“ˆ Financial ML: Supervised learning for trading signals, meta-labeling frameworks, time-series cross-validation, walk-forward analysis
  • ā˜ļø Production Systems: Dockerized backtesting environments, automated model retraining, CI/CD for quant research
  • ⚔ High-Performance Computing: Vectorized pandas operations, parallel processing for large-scale simulations, computational optimization

About Me

  • šŸ’¼ Experience across quantitative research, capital markets, trading system environment and building products
  • šŸŽ“ BA Economics, MSc in Business Information Systems, MSc Financial Engineering
  • šŸ“ Mathematics studies
  • šŸŒ Based in Germany

I enjoy turning financial theory into clean, testable, and production-ready priducts.


Currently Building

  • crediqs Institutional credit risk infrastructure 1,437 tests Ā· 8 repos Ā· Live API SA-CCR Ā· xVA Ā· IFRS 9 ECL Ā· DeFi risk Ā· MiCA compliance → github.com/crediqs

Technical Stack

  • Languages: Python, SQL, Bash, React, Next.js
  • ML/Data: XGBoost, scikit-learn, PyTorch, pandas, numpy, scipy
  • Quant Finance: Risk modeling
  • Data Engineering: Apache Airflow, SQL databases, data validation pipelines
  • DevOps: Docker, Git, AWS/Azure/GCP, CI/CD
  • Research: Jupyter, matplotlib, seaborn, SHAP, statistical analysis
  • Agent Frameworks: Ā· LangGraph Ā· Claude Code (Native/MCP) skills development Ā· LLM & non LLM agents

Pinned Loading

  1. crediqs/.github crediqs/.github Public

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