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Arnav GargAG
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Arnav Garg

@arnavgarg

Computer science and data science student skilled in data analytics, BI, and full‑stack development.

United States
Message

What I'm looking for

I am seeking analytics or BI roles where I can build scalable data pipelines and dashboards, collaborate with cross-functional teams, and drive measurable business impact.

I am a computer science and data science undergraduate combining technical rigor with practical analytics experience. I have delivered Power BI dashboards and automated ETL workflows that uncovered $56M+ in growth opportunities and improved reporting efficiency.

My internship and independent projects span data engineering, business intelligence, and full‑stack development — from PostgreSQL-backed dashboards and R Shiny apps to Node.js APIs and JavaScript front ends. I hold certifications in Python and Salesforce and regularly apply SQL, Python, R, DAX, and Power Platform tools.

I bring a results-oriented mindset, strong communication from consulting and leadership roles, and a focus on building scalable analytics solutions that translate data into business impact.

Experience

Work history, roles, and key accomplishments

IP
Current

Full-Stack Developer

Independent Project

Sep 2024 - Present (1 year 9 months)

Developed a full-stack quiz application with user authentication, CRUD quiz management, and a Node.js/Express API interacting with MongoDB to persist users and quiz history.

IP

Independent Data Analyst

Independent Project

May 2025 - Jun 2026 (1 year 1 month)

Built and deployed an R Shiny app analyzing 5 years of NBA play-by-play data to identify top clutch players, engineering tidyverse pipelines and interactive Plotly visuals.

Education

Degrees, certifications, and relevant coursework

University of Wisconsin - Madison logoUM

University of Wisconsin - Madison

Bachelor of Science, Computer Science and Data Science

Grade: GPA 3.57

Pursuing a Bachelor of Science in Computer Science and Data Science with a 3.57 GPA and coursework in algorithms, linear algebra, databases, and machine learning; expected graduation May 2027.

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