I build smart data solutions and love turning ideas into impact.
Developed a predictive model to forecast stock prices using historical data. Implemented feature engineering with technical indicators and trained models including XGBoost and LSTM to achieve robust time series predictions.
Tools: Python, Pandas, scikit-learn, XGBoost, LSTM, matplotlib
View on GitHubAnalyzed the effect of climate variables on global crop yields using machine learning models. Built predictive models including Random Forest, Gradient Boosting, and Neural Networks to estimate crop productivity under various climate scenarios.
Tools: Python, Pandas, scikit-learn, TensorFlow, Random Forest, XGBoost, Neural Networks, matplotlib
View on GitHubI’m a Data Scientist with a Master’s in Data Science from Pace University and over 3.6 years of experience in data engineering and analytics. I specialize in building scalable ML models and pipelines using Python, SQL, and cloud tools like AWS. I’m passionate about applying machine learning to solve real-world challenges — especially in climate, finance, and healthcare domains. Currently, I’m seeking full-time opportunities in data science, machine learning engineering, or analytics roles where I can make a real impact.
📧 Email: sowmyayalavarthi98@gmail.com
💼 LinkedIn: linkedin.com/in/sowmya-yalavarthi
💻 GitHub: github.com/SOWMYAYALAVARTHI
📄 Resume: Download Resume (PDF)