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jaswantjayacumaar/README.md

👋 Hi, I'm Jaswant Jayacumaar

Detail-oriented Data Analyst skilled in Python (Pandas, NumPy) and SQL for building and maintaining data pipelines, executing ETL workflows, and ensuring data quality. Proficient in data visualization using Power BI software for interactive dashboards and the Matplotlib package for custom plots to support data-driven decisions. I also bring hands-on expertise with Linux, VS Code, and Git for efficient development and version control. Trained in collaborating with cross-functional teams to deliver actionable insights to diverse stakeholders, meeting client needs. Possesses an engineering mindset with a strong ability to balance conflicting priorities, ensuring high quality outcomes through teamwork and analytical problem-solving.

🛠️ Languages and Tools

Languages & Libraries: Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, TensorFlow, LightGBM), SQL

Data Engineering: ETL workflows, Data preprocessing, Automation, Feature scaling

Development Tools: VS Code, Jupyter Notebook

Analytics & Visualisation: Power BI, MS Excel, Google Sheets, Celonis

Version Control: Git, GitHub

Development & Environments: Linux(Ubuntu), Windows

Core Skills: Data Wrangling • EDA • Predictive Modeling • Visualisation • Statistical Analysis • Process Mining


Python Git VS Code Linux Jupyter LaTeX Power BI

📂 Featured Projects

🔬 Pulsar Timing Analysis

Python-based analysis of 500+ pulsars using MCMC, waveform fitting, and automated EDA to explore timing residuals and trends.

🌴 PowerBI Project - Plant Co.

Designed an interactive Plant Co. Performance Dashboard using Power BI, employing diverse plots and DAX queries to analyse sales trends, optimize profitability, and provide actionable insights for data-driven decisions

⚽ Fantasy Football Forecast Tool

Machine learning pipeline to predict player performance using multiple classification models and historical data.

🌌 Gravitational Wave Signal Classification

Deep learning project using CNNs and TensorFlow to classify lensed vs. unlensed gravitational wave signals based on simulated waveforms. Developed and validated models with PyCBC data, focusing on preprocessing, tuning, and cross-detector performance testing.

📬 Let's Connect

Feel free to reach out via email or connect on LinkedIn or explore more of my work here on GitHub.


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  1. PowerBI-Plant_Co PowerBI-Plant_Co Public

    Interactive performance dashboard using PowerBI for a plant company, Plant Co.

  2. Pulsar-Timing-MeerKAT Pulsar-Timing-MeerKAT Public

    Timing Pulsars with the Thousand Pulsar Array on MeerKAT

    Jupyter Notebook

  3. Classyfying-LensGW-DL Classyfying-LensGW-DL Public

    Use of Deep Learning to Classify Lensed and Unlensed Gravitational Waves

    Jupyter Notebook

  4. Fantasy-Football-Forecast-Tool Fantasy-Football-Forecast-Tool Public

    Fantasy Football Forecast Tool

    Jupyter Notebook

  5. Cognizant-AI-Internship Cognizant-AI-Internship Public

    Cognizant AI Training and Internship Program

    Jupyter Notebook

  6. KPMG-Data-Analytics-Internship KPMG-Data-Analytics-Internship Public

    KPMG Data Analytics Internship