Tulsi Mishra

I’m a Data Science graduate with hands-on experience building end-to-end ML pipelines—turning raw data into decisions and deploying models that stay reliable in real workflows.

I’ve engineered modular data pipelines for scalability and maintainability, and I focus on strong fundamentals like exploratory data analysis, feature engineering, model evaluation, and hyperparameter tuning to improve predictive performance.

In projects, I designed an end-to-end modular ML pipeline for student performance prediction with Streamlit Cloud for real-time, user-friendly predictions, and I built a network security anomaly detection system with MongoDB-backed ingestion, MLflow/DagsHub for experiment tracking, and Dockerized deployment.

As a Data Analyst Intern, I built Python-based data pipelines to clean, process, and structure large datasets and created visualizations using Matplotlib and Seaborn to uncover actionable trends. I’m now actively seeking an entry-level Data Scientist / ML Engineer role where I can deliver measurable business impact through practical machine learning and MLOps-ready pipelines.