I am a passionate & aspiring Data Analyst from Goa, India, dedicated to optimizing queries and finding the stories & why hidden within numbers. I transform raw data into clear, actionable business strategies using analytical tools.
- 🎓 B.Tech in Electrical Engineering
- 📊 Passionate about Data Analytics & Business Intelligence
- 💼 Experienced in Power BI Dashboard Development
- 🌱 Currently strengthening skills in SQL, Python & Data Engineering
- 📈 Love transforming raw data into actionable insights
- 🎯 Targeting Data Analyst roles at top companies
- ⚡ Fun Fact: I enjoy turning complex datasets into simple business stories
Here is a look at what I've been building across my repositories:
- Built an interactive Streamlit dashboard for loan & card portfolio analytics with an XGBoost default scorer.
- Analyzes borrower behavior, repayment performance, risk distribution, and revenue impact.
- Combines Python, SQL, and machine learning to surface high-risk segments and portfolio-level insights.
- Designed for business users to explore loan performance and default risk interactively.
- Analyzes a bank’s loan portfolio to understand borrower behavior, repayment performance, risk distribution, and revenue impact.
- Uses Python for data processing and visualization to identify high-risk segments.
- Highlights patterns in loan defaults, repayment delays, and customer risk profiles.
- Supports data-driven credit risk monitoring and portfolio decision-making.
- Focuses on analyzing vendor performance, inventory lifecycles, and sales profitability.
- Establishes a robust ETL pipeline to ingest raw inventory and purchase data into a relational database.
- Identifies underperforming vendors, slow-moving inventory, and margin improvement opportunities.
- Delivers actionable insights for procurement and inventory optimization.
- Analyzes why shipments miss scheduled timelines and where operational improvements have the greatest commercial impact.
- Transforms operational data into performance intelligence using Python and SQL.
- Tracks delivery delays, carrier performance, and bottleneck patterns across the supply chain.
- Helps prioritize fixes that improve service levels and reduce operational cost.
- Analyzed 8,523 retail transactions generating $1.20M+ in total sales across multiple outlet types and product categories.
- Built an executive Power BI dashboard featuring 15+ KPIs, including Total Sales, Average Sales, Outlet Performance, Customer Ratings, and Inventory Distribution.
- Developed advanced DAX measures and interactive visualizations to identify top-performing product categories and revenue-driving outlets.
- Delivered actionable business insights that improved visibility into sales trends, outlet efficiency, and customer purchasing behavior.
- Designed and developed multiple end-to-end Power BI solutions covering data extraction, transformation, modeling, and business reporting.
- Created 15+ DAX measures and KPIs to track revenue, profitability, customer performance, and operational efficiency.
- Implemented star-schema data models and optimized report performance using Power Query and advanced DAX techniques.
- Built interactive dashboards with drill-through functionality and dynamic filtering, enabling data-driven decision-making for stakeholders.
- Analyzed 1,000+ customer transactions across multiple Walmart branches to evaluate revenue performance and consumer purchasing behavior.
- Performed exploratory data analysis using SQL and Power BI to uncover sales trends, customer preferences, and product demand patterns.
- Identified peak sales periods, top-performing product lines, and branch-level performance opportunities through data-driven insights.
- Developed an interactive business dashboard with 10+ key performance metrics supporting strategic planning and operational monitoring.
- Analyzed survey data from 630+ data professionals across various countries, experience levels, and job roles.
- Built a fully interactive Excel dashboard using Pivot Tables, Power Query, Slicers, and Dynamic Charts to visualize compensation trends.
- Automated data preparation and transformation workflows, reducing manual analysis effort by approximately 80%.
- Generated insights into salary benchmarks, high-paying skills, and regional compensation differences within the data analytics industry.
- Peak Remote Salary Identified: $650,000 (Top-tier remote Data Analyst roles).
- High-Compensation Salary Floor: $184,000 minimum threshold for the top 10 highest-paying roles.
- Top-Paying Skill Premium: Up to $208,172 average yearly salary for specialized data pipeline skills (PySpark).
- Core Skill Market Baseline: Highly demanded programming skills (Python, R) maintain an average baseline salary of ~$101,000.
- LendScope — Bank Loan & Card Portfolio Analytics Dashboard — Interactive Streamlit dashboard with an XGBoost default scorer for loan & card portfolio analytics.
- Netflix SQL Business Analysis — Explores 8,807 Netflix titles using PostgreSQL to solve 15 business questions.
- Customer Shopping Analysis — End-to-end analysis of 3,900 customer purchase records.
- Electric Vehicle Population Analytics — Interactive Tableau analysis of EV registration data.
🏅 Microsoft Power BI Data Analyst
🏅 SQL for Data Analytics
🏅 Data Analytics Professional Certificates
🏅 Python for Data Analysis
Feel free to reach out if you want to collaborate on a data project, discuss query optimization, or talk about market insights!