Jai Gaikwad
Data Science and Machine Learning @Nia.One
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WORK HISTORY
Data Science and Machine Learning @Nia.One
EDUCATION
Veermata Jijabai Technological Institute (VJTI)
Bachelor's degree, Information Technology
Pune Vidhyarthi Griha's College of Engineering and Technology Pune
12th
Indian Institute of Technology, Kanpur
Bachelor's degree, Chemical Engineering
ABOUT JAI GAIKWAD
I am a 3rd year undergraduate student at IIT Kanpur with a deep interest in quantitative research, data analytics, and financial modeling. My academic foundation blends engineering rigor with applied statistics, time series forecasting, and computational techniques, which I’ve actively applied in project-based learning and research work. Through hands-on experience, I’ve developed strong technical fluency in Python, NumPy, pandas, scikit-learn, TensorFlow, and data visualization tools like Power BI, Matplotlib, and Seaborn.I have implemented advanced time series forecasting models, including ARIMA, SARIMAX, and GARCH, and built deep learning architectures such as multi-layer LSTM networks to model non-linear price dynamics, forecast short-term returns, and capture volatility patterns. My projects emphasize data preprocessing, rolling-window validation, lag-based feature engineering, and inverse-scaling techniques to simulate real-market deployment. I regularly benchmark model performance using RMSE, MSE, AIC, and Sharpe ratio to assess signal quality and forecasting accuracy.In addition to quant modeling, I have strong exposure to business analytics and decision science. I’ve used SQL, Excel, and Power BI to design interactive dashboards, clean and query large datasets, and generate insights that drive strategic recommendations. My coursework and certifications span Probability & Statistics, Linear Algebra, Econometrics, Financial Engineering, Machine Learning, and Time Series Analysis, all of which strengthen my ability to bridge quantitative theory with practical data problems.I am passionate about applying mathematical thinking, programming, and algorithmic logic to solve complex problems across financial markets, trading strategies, portfolio optimization, and business operations. I thrive in fast-paced, data-intensive environments and am actively seeking full-time or internship opportunities in quantitative research, data analytics, or financial analysis roles where I can contribute through modeling, experimentation, and data-driven innovation.
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