🀹 Skills

πŸ“₯ Data Collection & Querying MySQL, Excel
🧹 Data Cleaning & Validation Pandas, NumPy, Excel
πŸ“Š Analysis & Manipulation Python, Jupyter Notebook, Pandas, NumPy
πŸ“ˆ Visualization Tableau, Power BI, Matplotlib, Seaborn
πŸ€– Machine Learning Scikit-learn (sklearn)
πŸ› οΈ Tools & Platforms Git/GitHub, Excel, Jupyter Notebook
πŸ’‘ Generative AI ChatGPT for productivity, storytelling, and rapid ideation
🌐 Languages English, Hindi

πŸ§‘β€πŸŽ“ Education

πŸŽ“ Exam/Degree 🏫 Institution πŸ“… Year ⭐ Score
Common Admission Test (CAT) Indian Institutes of Management (IIMs) 2024 Percentile: 96.06
B.E., Electronics and Communication (ECE) UIET, Panjab University, Chandigarh 2024 CGPA: 8.59
Class 12th Govt. Model Sr. Sec. School, Chandigarh 2020 92.8%

πŸ”§ Work Experience

Freelance Data Analyst

Independent Projects | Remote
Jan 2025 – Present

  • πŸš€ Delivered end-to-end analytics solutions including automated BI pipelines, MySQL databases, and interactive Power BI dashboards across sales and sports domains.
  • πŸ” Engineered data validation frameworks and exploratory analysis workflows to ensure data quality and uncover actionable insights.
  • πŸ’‘ Leveraged AI tools to enhance documentation quality, workflow efficiency, and project delivery speed.

Research Analyst Intern

GreyB Research Pvt. Ltd. | Punjab, India
Jan 2024 – June 2024

  • πŸ” Conducted in-depth prior art searches using Derwent and Orbit across global patent and technical databases.
  • πŸ“ Delivered comprehensive search reports highlighting key insights, claim charts, and critical prior references to support legal and R&D teams.
  • βœ… Contributed to patentability, invalidity, and freedom-to-operate (FTO) assessments, enabling informed IP decisions.
  • πŸ… Certified as a Specialist-level Patent Analyst for exceeding quality and speed benchmarks.

πŸš€ Projects


πŸ“Š Sales Health Monitor – Automated BI Pipeline

  • πŸš€ End-to-end automated BI pipeline processing 800K+ retail transactions.
  • πŸ—„οΈ Engineered MySQL star schema database with 8 tables and 11 analytical views for scalable data modeling.
  • πŸ” Built adaptive anomaly detection framework reducing false alerts by 85% through percentile-based thresholds.
  • πŸ“Š Developed 4 multi-page Power BI dashboards with custom DAX measures for executive, risk-monitor, customer, and geographic intelligence.
  • πŸ§ͺ Conducted comprehensive EDA using Python (Pandas, NumPy, Matplotlib, Seaborn) uncovering seasonality patterns and customer segmentation.
  • βš™οΈ Designed modular automation workflows for data generation, cleaning, validation, and dashboard refresh cycles.
  • πŸ’‘ Dashboard enables stakeholders to track YoY growth, revenue drivers, and high-value customer segments in real-time.
Executive Overview Anomaly & Risk Monitor Customer Intelligence Geographic & Product Performance

🏏 IPL Data Analysis (Season 2024 and 2025)

  • 😎 Interactive Power BI Dashboard built for IPL 2024 & 2025 seasons.
  • πŸ—ƒοΈ Extracted datasets on seasons, players, and matches using structured SQL queries.
  • πŸ§ͺ Performed EDA at player and team level using Python (Pandas, Matplotlib, Seaborn).
  • πŸ“Š Created dynamic KPIs, trend charts, and filters in Power BI for match behavior and performance.
  • 🧠 Used ChatGPT to assist in storytelling, querying logic, and content generation.
  • πŸ’‘ Dashboard designed to help stakeholders explore season insights, team performance, and player impact.
IPL Overview Team Performance Players Performance Match Flow

πŸ›οΈ Sales Data Comparison & Analysis (2023–2024)

  • 🐍 Created realistic synthetic sales data for 2023 and 2024 using Faker, NumPy, and Python logic blocks.
  • 🧹 Cleaned and structured datasets to match realistic product, customer, and date patterns.
  • πŸ“Š Built a multi-page Power BI dashboard with maps, tooltips, slicers, KPIs, and charts.
  • πŸ€– Used ChatGPT as a co-pilot for debugging, markdown writing, and visual planning.
  • πŸ” Focused on understanding growth trends, top customers, and product performance.
Sales KPI Dashboard Comparison Analysis View Tooltip Qtr-wise Summary

⚽ Football Striker Performance Analysis

  • 🧠 Explored what separates an average striker from an exceptional one using data on 500 professional footballers.
  • πŸ§ͺ Used Python (pandas, seaborn, matplotlib, sklearn, statsmodels) for EDA, hypothesis testing, clustering, and logistic regression.
  • 🧹 Applied encoding, imputation, and scaling techniques for preprocessing.
  • πŸ“ˆ Clustered players into β€œTop Strikers” and β€œRegular Strikers” using K-Means.
  • πŸ€– Leveraged Generative AI (ChatGPT) to validate logic, speed up exploration, and clean documentation.

Football Striker Dashboard


🏠 House Sales Analysis Dashboard

  • πŸ“Š Designed an interactive Tableau dashboard to analyze house sales in King County.
  • 🎯 Implemented filters and slicers for dynamic insights into pricing, sales trends, and demographics.
  • πŸ—ΊοΈ Used maps, KPIs, and bar charts for visual exploration.
  • πŸ§‘β€πŸ’Ό Tailored for real estate stakeholders to derive actionable insights.

House Sales Dashboard