I'm a quant-oriented developer building at the intersection of
finance, statistics, and machine learning.
- ๐ Core focus: Stochastic modeling, Monte Carlo simulation, timeโseries forecasting, and risk analytics
- ๐ค ML focus: Probabilistic inference, anomaly/fraud detection, imbalanced classification
- ๐ Data stack: Feature engineering, financial dashboarding, backtesting pipelines
- ๐ญ Currently exploring: LLMs applied to financial NLP, deep learning for ฮฑโsignal generation
- ๐ค Open to collaborate on: Quant research, neural network training, financial data pipelines
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Core inference experiments: MLE, Bayesian estimation, and probabilistic modeling workflows foundational to quant research. |
End-to-end financial modeling: stochastic price simulation, forecasting, risk analysis, and strategy backtesting. |
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Fraud classification on highly imbalanced transactional data. Focus on precision-recall tradeoffs, SMOTE, and ensemble methods. |
Personal finance tracker with embedded analytics, trend visualizations, and spending pattern dashboards. |
- ๐งฉ Inference-learning โ Core inference experiments (MLE/Bayesian ideas) used in my modeling workflow.
https://github.com/AaryanAnand10/Inference-learning - ๐น Finance-Modeling โ Financial modeling experiments (forecasting, risk analysis, backtesting).
https://github.com/AaryanAnand10/Finance-Modeling - ๐ก๏ธ Credit Card Fraud Detection โ Fraud/anomaly classification on transaction data (precisionโrecall focus).
https://github.com/AaryanAnand10/Credit_Card_Fraud_Detection- - ๐ฐ Income-Tracker โ Personal finance tracker with analytics and visualizations.
https://github.com/AaryanAnand10/Income-Tracker-
"In God we trust; all others must bring data." โ W. Edwards Deming