Data Analyst with less than a year in Python, SQL, and Power BI
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Data-focused BCA student with hands-on experience building end-to-end analytics pipelines using Python, SQL, and Power BI. Certified by IIT Roorkee and IIT Guwahati in Data Analytics. Passionate about transforming raw data into business decisions through ML-powered intelligence systems.
BSSS, Bhopal
Bachelor of Computer Applications (BCA)
August 1, 2024 – Present
Bal Bhawan School, Bhopal
Class 12th · Informatics Practices
June 1, 2023 – May 31, 2024
Cybrom Technology
Data Analyst Intern
May 1, 2026 – Present
Bhopal, Madhya Pradesh, India
UPI Transaction Intelligence System
June 17, 2026 – Present
Built an ETL pipeline using Pentaho Spoon to load 50,000 UPI transactions (6.8Cr volume) into MS SQL Server; wrote 50+ analytical queries using CTEs, window functions (RANK, DENSE_RANK, ROW_NUMBER), multi-table JOINs, and stored procedures - identifying Education (0.66%) and Food (0.59%) as the highest fraud-rate merchant categories. Performed EDA using Pandas, Matplotlib, and Seaborn; uncovered that Pune and Delhi are the riskiest cities by fraud rate, 7pm is the peak fraud hour, and velocity-burst transactions show 2.4x higher fraud probability than normal transactions. Engineered 6 behavioral features (amount z-score, geo-distance, velocity, device trust, hour risk); applied Isolation Forest (Scikit-learn) to flag 2,500 anomalies; built a custom 1-5 trust rating using scipy rankdata + pd.qcut combined into a final 0-1000 trust score. Designed a 5-tier real-time decision engine routing 17,165 transactions to Auto-Approve and 33 high-risk transactions to Block; connected scored SQL Server data to a live Power BI dashboard visualizing fraud distribution, city-level risk, and merchant category analysis.
View ProjectZepto Product Analytics
June 17, 2026 – Present
Engineered a complete SQL pipeline on a Zepto grocery dataset - schema design, NULL/duplicate quality checks, price normalisation - delivering 8 business-focused queries revealing category revenue, top-discount rankings, and high-MRP out-of-stock alerts. Classified products by weight tier using CASE WHEN segmentation and ranked by price-per-gram; produced a fully documented GitHub repository with README, schema reference, and query-level business context. Surfaced restocking and promotional opportunities by engineering a complete SQL pipeline on a Zepto grocery dataset - including schema design, NULL/duplicate quality checks, and price normalisation from paise to rupees. Delivered 8 business-focused analytical queries revealing estimated category revenue, top-discount product rankings, and high-MRP out-of-stock alerts - enabling data-driven inventory and marketing decisions.
Data Analytics Using Python
NPTEL, IIT Roorkee
June 1, 2026 – Present
Python for Data Science
NPTEL (Elite)
June 1, 2026 – Present
Advanced Certification in Data Analytics
E&ICT Academy, IIT Guwahati
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from fraud detection in UPI transactions to product analytics for a grocery dataset, indicates adaptability and a broad interest in applying data analysis across different business domains. The focus on delivering actionable business insights aligns well with a results-oriented culture. The candidate's current internship and ongoing education suggest a commitment to growth and a willingness to learn within a professional environment. The skills acquired and applied are highly relevant to a Data Analyst role, indicating a good fit for a data-driven team.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through project descriptions, particularly in identifying fraud patterns and optimizing product analytics. The detailed project documentation suggests good organizational skills. While direct evidence of teamwork or stress handling is not provided, the complexity of the projects implies a capacity for independent work and managing project scope. The candidate's proactive pursuit of certifications indicates a strong drive for continuous learning and professional development.