Aayush Bajaj's CV

Data Analyst

Education

Statistical Analysis: Hypothesis Testing, Regression, Time Series, Experimental Design, A/B Testing, Bayesian Methods
Data Engineering: SQL, PostgreSQL, ETL Pipelines, Data Warehousing, Azure SQL, pgvector
Analytics & Visualisation: Python, Pandas, NumPy, Matplotlib, Seaborn, Statistical Modeling, Data Cleaning
Cloud & Infrastructure: Azure, Docker, RESTful APIs, Data Pipeline Orchestration
Development Tools: Git, Jupyter, Linux/Shell, Version Control, Automated Testing

Oct 2024 – June 2025
Implemented and compared 2D/3D state-of-the-art architectures; achieved class-leading Dice score of 78% (full marks).
Reproduced nnU-Net end-to-end on Nvidia H200/A200; published technical report with ablation studies.
Deployed to KiTS19 official leaderboard: ranked #57 globally with Dice score of 0.9129 through systematic hyperparameter optimisation.

Kaggle
Implemented U-Net from scratch (31M parameters); combined Dice + Focal loss for 97% class imbalance.
Achieved 0.71 IoU after morphological post-processing; parallelized training on CUDA-enabled HPC.

Aug 2024 – present
Comprehensive Jupyter notebooks for supervised/unsupervised learning with statistical rigor.
Version-controlled experiments demonstrating data preprocessing, feature engineering, and model validation.

May 2023 – present
Automated publishing pipeline built with Hugo; deployed behind Nginx with HTTPS.
Comprehensive ML documentation following Zettelkasten methodology for knowledge graphs.

2024 – present
Sydney, NSW
Deployed data infrastructure and analytics pipelines for client web applications.
Configured database systems, ETL workflows, and monitoring dashboards for production environments.