- 💬 I'm a quantitative researcher in systematic investment by day, and data scientist/software developer by night
- 🔭 I’m currently working on building software and models to draw insights from data and help guide busienss decisions
- 🌱 I’m currently learning machine learning/deep learning/NLP/big data/statistical models, and the list goes on
- 👯 I’m looking to collaborate on interesting Kaggle project!
- 🤔 I’m looking for help with finding the next interesting opportunities!
- 📫 How to reach me: sarahwang688@berkeley.edu
- 😄 Personal website: https://sarah-yifei-wang.github.io/
- ⚡ Fun fact: I'm also the winner of Miss Asia Canada :)
- ✨ Achievement
- ⭐ NLP: Aspect-based Sentiment Analysis in Document - FOMC Meeting Minutes
- ⭐ React-Native: Target-Sum-Game
- ⭐ sklearn: Housing Sales Prediction from Demographic Data
- ⭐ Stats: Regression Study on Covid Situations
- ⭐ Neural Networks: Realized Volatility Prediction
- ⭐ React - Website for Restaurant Management
- ⭐ React-Native - Mobile for Interactive Menu and Ordering Service
- ⭐ Optimization - Mean Variance Optimization with Transaction Cost
🎯
Focusing
⭐Machine Learning | Quantitative Finance | Software Engineer
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CPP Investment
- https://sarah-yifei-wang.github.io/
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Mean-Variance-Optimization-with-Transaction-Costs
Mean-Variance-Optimization-with-Transaction-Costs Public -
Neural-Network-with-Financial-Time-Series-Data
Neural-Network-with-Financial-Time-Series-Data PublicForked from BenjiKCF/Neural-Net-with-Financial-Time-Series-Data
This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow
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Optiver-Realized-Volatility-Prediction
Optiver-Realized-Volatility-Prediction PublicJupyter Notebook
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