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parthkaushal18/README.md

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πŸ“ Sydney, Australia πŸ‡¦πŸ‡Ί | πŸ“§ parth.kaushal31@gmail.com

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🧠 About Me

  • πŸŽ“ Honors of Engineering in Computer Engineering @ University of New South Wales (UNSW), Sydney (2025–2027) | WAM: 75
  • πŸŽ“ Bachelor of Engineering in Computer Engineering @ Thapar Institute of Engineering and Technology, India (2023–2025) | CGPA: 8.5
  • πŸ’Ό Former Software Engineering Intern @ Nokia & Macron Ventures
  • πŸš€ Passionate about building robust backend architectures, scalable ML pipelines, and interactive data visualization tools.
  • πŸ›οΈ Core Member @ Association for Computing Machinery (ACM) β€” Led cross-functional teams and trained 1,000+ students.

πŸš€ Languages and Tools

Python
Python
JavaScript
JavaScript
React
React
Java
Java
C++
C++
SQL
SQL
AWS
AWS
GitHub
GitHub
Docker
Docker
Kotlin
Kotlin
TensorFlow
TensorFlow
Scikit-Learn
Sklearn
FastAPI
FastAPI
Node.js
Node.js
Git
Git
OpenCV
OpenCV
PostgreSQL
PostgreSQL
Linux
Linux

πŸ’Ό Professional Experience

🌐 Macron Ventures Pvt. Ltd. | Product Development Intern (Dec 2024 – Aug 2025)

  • Developed community-driven events platforms, utilizing performance analytics and audience segmentation.
  • Boosted platform engagement by 90% through data-backed digital outreach strategies.

πŸ“± Nokia India Pvt. Ltd. | Software Engineering Intern (May 2024 – Nov 2024)

  • Engineered telecom software solutions in Python, Java, and SQL inside Agile teams, optimizing system latency.
  • Identified performance bottlenecks and designed backend log analysis and database queries.

πŸ›οΈ ACM Student Chapter | Core Member (Sept 2023 – June 2025)

  • Led a 50+ member cross-functional team deploying web platforms and managing digital infrastructure.
  • Delivered 20+ technical workshops on programming and AI/ML to 1,000+ students.

πŸš€ Projects

Project Description Stack Status
πŸ“ˆ Financial Data Dashboard Real-time ASX financial data ingestion, cleaning, trend visualization, and anomaly detection. Python Β· Pandas Β· Streamlit πŸ”— Code
πŸ›‘οΈ Fraud Detection ML Pipeline End-to-end pipeline implementing SMOTE for credit card fraud classification, yielding 95%+ accuracy. Python Β· Scikit-Learn Β· Streamlit πŸ”— Code
🌿 EU CBAM Compliance SaaS Automatically generates regulatory EU CBAM XML submission reports for exporters in minutes. React.js Β· FastAPI Β· XML πŸ”— Code

πŸ“Š GitHub Stats


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πŸ’¬ Let's connect and build something that matters!

"I don't just train models. I deploy them."

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