Adele Shahi

About Adele Shahi

I’m a data and strategy professional with 14+ years of experience in business intelligence, quantitative modeling, and ERP-integrated analytics. My strength lies in building forecasting models, KPI frameworks, and interactive dashboards that drive business outcomes.At Proof Trading (NYC), I design econometric and machine learning models to predict closing auction sizes and support high-frequency trading strategy. Previously, I led data initiatives at CUNY and FANAP, aligning analytics with institutional and industry-wide strategic goals across finance, education, and manufacturing sectors.My work bridges business insight with technical rigor—leveraging tools like Python, SQL, Power BI, and panel data models to turn complex data into clear, actionable intelligence.Let’s connect if you’re exploring BI transformation, predictive modeling, or strategic decision support through data.

Experience

1. Quantitative Researcher

   Proof Trading

   Feb 2023 — Present · New York, NY, US

   Led development of systematic forecasting frameworks for U.S. equity closing auctions, modeling ‎auction size dynamics and liquidity concentration patterns across multi-year datasets.‎• Built deployable predictive models (GLM, GEE, GLS, ensemble residual modeling) reducing out-of-‎sample forecast error from 0.35 to 0.10 across segmented liquidity regimes.‎• Designed regime-aware signal evaluation processes using changepoint detection and rolling stability ‎metrics to differentiate structural shifts from transient microstructure noise.‎• Assessed signal robustness under varying liquidity conditions and collaborated with trading teams on ‎practical deployment considerations.‎• Developed ETF-to-symbol proxy models via Lasso regression with inverse notional weighting to enhance ‎cross-sectional signal extraction under heteroskedastic conditions.‎• Implemented structured cross-validation pipelines (time- and symbol-split) to mitigate overfitting and ‎structural break sensitivity.‎• Co-authored internal white paper formalizing auction forecasting methodology.‎

Education

• The City University of New York

  Master of Engineering - MEng, Data Science Engineering

• National Organization for Development of Exceptional Talents (Sampad)

  Diploma of Education, Mathematics

• Amirkabir University of Technology - Tehran Polytechnic

  Master's degree, Industrial Engineering

• Isfahan University of Technology

  Bachelor's degree, Statistics

• Cisco Networking Academy

  Cybersecurity certificates