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Data Analyst with 1+ years in SQL, Python, and Power BI for data-driven insights.
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Entry-level data analyst with hands-on experience analysing datasets up to 145K records across telecom, logistics, and e-commerce. Skilled in SQL (joins, window functions, CTEs), Python (pandas, NumPy), Tableau, Power BI, and Excel, with training in A/B testing and foundational statistics. Completed a 9-month Data Analytics with Generative AI programme and a Deloitte virtual internship, delivering three end-to-end projects that transformed raw data into clear, actionable insights for non-technical stakeholders.
NIST University
Master of Computer Applications (MCA)
August 1, 2023 – June 30, 2025
Coding Wise
Data Analytics Trainee
January 1, 2025 – Present
India
Deloitte (via Forage)
Data Analytics Virtual Intern
January 1, 2025 – March 1, 2025
India
Customer Churn Analysis & Prediction
January 1, 2026 – June 1, 2026
Problem: A telecom company was losing 27% of customers with no way to identify who was at risk. Analysed 7,032 customer records, found month-to-month contracts churn at 43% vs. 3% on two-year plans, a 15x difference that shaped the retention strategy. Identified fibre optic users and customers without tech support churning at ~42% - root cause was service quality, not pricing. Built a predictive analytics model in Python (pandas, scikit-learn) that flagged 1,703 high-risk customers before churn, enabling proactive outreach. Delivered an interactive Power BI dashboard using DAX measures to track churn by contract type, service, and risk level - empowering data-driven retention decisions.
Food Delivery Performance Analysis
January 1, 2026 – June 1, 2026
Problem: Delivery delays across 145K+ orders with no root-cause visibility. Queried over 145,000 order records in SQL using window functions and CTEs to pinpoint delay patterns by region and time period. Discovered high-workload periods increased delivery time by 10.6% - from 44.4 to 49.1 minutes - with rush hour peaking at 52.4 minutes. Built a dynamic Power BI dashboard with custom calculated fields and slicers to visualise delays by time of day, workload, and food category. Recommended a dynamic resource allocation model for peak hours - directly addressing the root cause of delays.
E-commerce Sales & Pricing Analysis - Flipkart
January 1, 2026 – June 1, 2026
Problem: No visibility into product performance or whether discounts were actually working. Analysed 1,495 products across 387 brands using SQL, uncovered pricing gaps, category dominance (clothing at 28%), and over-discounting in women's fashion (252K total discounts). Identified a premium pricing opportunity in laptops being missed due to blanket discount policies. Built a Power BI dashboard tracking pricing, discounts, and category trends - turning scattered data into a clear business picture. Recommended reducing discounts in over-indexed categories to recover margin without hurting sales volume.
Advanced Data Analytics with Generative AI
Coding Wise
June 1, 2026 – Present
SQL
HackerRank
June 1, 2026 – Present
Data Analytics Job Simulation
Deloitte via Forage
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's projects cover diverse domains (telecom, food delivery, e-commerce), indicating adaptability and a broad interest in applying data analytics to various business challenges. Their experience with both structured training (Coding Wise) and virtual internships (Deloitte) suggests a proactive learning attitude and exposure to different work environments. The explicit mention of A/B testing and hypothesis testing aligns with a data-driven culture.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills by identifying root causes and proposing data-driven solutions in their projects. Their ability to deliver end-to-end analytics projects and present findings to non-technical stakeholders indicates good communication and operational fit for roles requiring actionable insights. The focus on business impact in project descriptions suggests a results-oriented approach.