An aspiring Graduate Student focused on Computer Science, Data Science, and Data Analytics Engineering. I specialize in building interconnected software systems, optimizing machine learning pipelines, and automating ETL workflows.
Instead of building isolated apps, I dedicated my final year to architecting a single, unified monolithic ecosystem that bridges the gap between Software Architecture and Data Intelligence.
- What it does: A production-ready E-commerce platform that handles user authentication, product catalogs, dynamic carts, and checkout pipelines. It serves as the root source of data generation.
- Tech Stack: Python, Django REST Framework, React.js, PostgreSQL, Node.js
- Impact: Optimized PostgreSQL indexing and query architecture to reduce page load latency by 40% under peak simulated traffic.
- What it does: Pulls raw transactional and user behavior logs from the platform to run advanced analytics. It segments users into target personas and catches fraudulent transactions in real-time.
- Tech Stack: Python, Jupyter Notebooks, Scikit-Learn, XGBoost, K-Means Clustering, SMOTE
- Impact: Handled severe class imbalance using SMOTE and trained an XGBoost model that achieved a 94% accuracy rate in detecting transactional anomalies.
- What it does: Automates the entire data lifecycle. It features an automated ETL pipeline that extracts fresh database logs, cleanses them, and loads them into an optimized data model for stakeholder visualization.
- Tech Stack: SQL, Power Query, Power BI, DAX
- Impact: Formulated complex DAX metrics (CLV, MoM Growth) and designed a Star Schema model, reducing manual executive reporting time by 85%.
- Languages: Python, SQL,
- Frameworks & Libs: Django, React, Node.js, Pandas, NumPy
- Databases & Tools: PostgreSQL, SQL Server, Git, GitHub
📫 Let's Connect: [https://www.linkedin.com/in/rajat-kumar-161144385]