LinkedIn | padma062@umn.edu | GitHub | Kaggle
I am a Master of Science in Analytics candidate at the University of Minnesota - Twin Cities (GPA: 3.6/4.0), expecting to graduate in May 2026. My professional background includes 2.5 years of experience at Tata Consultancy Services, where I drove significant improvements in operational efficiency and reporting accuracy as a Data Analyst and System Analyst. I have a strong foundation in building end-to-end data solutions, from engineering automated ETL pipelines with Python and SQL to developing predictive models using Scikit-learn, XGBoost, and TensorFlow.
I am actively seeking full-time opportunities in Data Science, Machine Learning Engineering, and Natural Language Processing, where I can apply my expertise in statistical modeling, big data technologies, and MLOps to solve complex, data-driven challenges.
- Predictive Modeling & Machine Learning: Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, Statistical Modeling, A/B Testing, Predictive Analytics.
- Data Engineering & Big Data: Advanced SQL, Python, PySpark, Hadoop, Hive, Kafka, ETL Pipeline Development, Data Wrangling.
- Databases & Cloud: PostgreSQL, MySQL, AWS (S3, EC2), Google Cloud Platform (GCP).
- Data Analysis & Visualization: Pandas, NumPy, R, Tableau, Power BI, Matplotlib, Seaborn.
Developed a high-performance XGBoost classifier (0.995 ROC AUC) on 8.9 million transactions, creating new rules projected to reduce fraud by 5-7%.
Engineered a real-time stock analysis pipeline using Kafka and Azure, deploying a Streamlit dashboard that achieved 90% predictive accuracy for key performance indicators.
Built a hybrid movie recommendation system using NLP (TF-IDF) and Collaborative Filtering to solve user churn by boosting engagement through personalized content.
Programming & Core Tools
Data Science & Machine Learning
Natural Language Processing (NLP)
Big Data & MLOps
Databases & Cloud
Data Visualization & BI
