Open to Data Analyst opportunities

Hi, I'm Aadit.
Data Analyst

I specialize in transforming raw data into actionable business insights through advanced analytics, predictive modeling, and automated reporting. I build scalable, production-ready pipelines that support strategic decision-making in real-world environments.

View My Work GitHub
Aadit Baldha

Education

Stevens Institute of Technology
Master of Science in Computer Science
Hoboken, NJ | GPA: 3.44/4
Exp. Dec 2025
Dharmsinh Desai University
Bachelor of Technology
Nadiad, Gujarat
Aug 2024

Data Analytics & ML Skillset

Languages & Querying
Python SQL (MySQL, Postgres) Google BigQuery
Data Science & Machine Learning
Scikit-learn Pandas NumPy Seaborn Jupyter Notebooks Natural Language Processing Transformers Reranking Models PyTorch
MLOps & Data Engineering
MLflow ZenML DVC Git GitHub GitHub Actions AWS S3
Certifications
AWS Cloud Practitioner AWS AI Practitioner

Professional Experience

Developer Intern (Data-Focused)
Benzinga
Detroit, MI
Dec 2023 – July 2024
  • Designed and optimized Python-based data pipelines supporting real-time analytics and internal reporting systems.
  • Improved data accuracy and system efficiency by resolving quality issues with cross-functional engineering and QA teams.
  • Delivered structured dashboards and analytical insights to support strategic decision-making.

Data Analytics & Machine Learning Projects

Customer Churn Analysis
Data Analysis • Predictive Modeling • Visualization

Built an end-to-end churn prediction workflow on 7,000+ customer records, transforming insights into retention-focused strategies.

75% Accuracy & 0.73 F1-score
Faster model iteration & reporting
Bankruptcy Risk Analytics
Financial Modeling • Automation • Version Control

Developed a predictive analytics system using 95 financial indicators with automated, reproducible pipelines.

30% improvement in prediction performance
Streamlined analysis and deployment
Text-Based Misconception Analysis (NLP)
NLP • Transformers • Ranking Models

Created an NLP pipeline to identify and rank student misconceptions by analyzing question-answer distractors.

Achieved MAP@25 score of 0.56
Reproducible & scalable inference flow