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Data Analyst with less than a year in Python, SQL & Power BI, specializing in business insights and
Computer Science professional with expertise in Python, SQL, Power BI, Excel, and Prompt Engineering. Experienced in data analysis, EDA, and dashboard development to deliver actionable business insights. Skilled at leveraging AI tools to drive data-informed decisions across finance, retail, and banking domains.
ITM University, Gwalior
B.Tech · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Sri Chaitanya Junior College
Intermediate · Mathematics, Physics, Chemistry
June 1, 2020 – May 31, 2022
Ushodaya Concept School, Proddatur
Secondary School Certificate
June 1, 2020 – May 31, 2020
Bank Customer Churn Analysis
June 1, 2026 – Present
Analyzed 10,000+ bank customer records to identify churn drivers — built RFM segmentation model in SQL classifying customers into 4 segments, identifying 2,343 At-Risk customers at 24.8% churn rate. Designed a 2-page interactive Power BI dashboard with KPI cards, slicers, and drill-down for executive-level reporting. Generated actionable insights: Germany churn rate (32%) is 2x higher than France/Spain; 50-60 age group identified at 56% churn risk enabling targeted retention campaigns.
Superstore Retail Sales Analysis
June 1, 2026 – Present
Performed end-to-end analysis on 10,000+ Superstore records using Python (Pandas, Matplotlib, Seaborn), uncovering category-wise and regional revenue trends. Built interactive Power BI dashboard with DAX measures for Total Sales, Profit %, and YoY Growth for executive reporting. Discount impact analysis revealed 20%+ discounts cause negative margins; West region led at 14.9% margin vs Central at 7.8%.
Data Analyst Course
Teks Academy
February 1, 2026 – Present
SQL Essential Training
LinkedIn Learning
January 1, 2026 – January 1, 2026
Prompt Engineering
LinkedIn Learning
January 1, 2026 – January 1, 2026
The candidate scored 90% on the Microsoft Analytics (Power BI) test, demonstrating a strong grasp of Power BI concepts and application.
Strengths
Limitations
Cultural Fit Analysis
The candidate's projects demonstrate a proactive approach to learning and applying data analysis techniques across different domains (banking, retail). Their academic background in Computer Science and Engineering, coupled with self-driven certifications, indicates a strong desire for growth and skill development. The inclusion of AI/Prompt Engineering skills suggests an interest in modern tools and methodologies, aligning with innovative team cultures. However, the lack of professional experience means cultural fit is primarily inferred from academic projects and listed soft skills.
Soft Skills & Operational Fit
The candidate lists strong soft skills such as Analytical Thinking, Problem Solving, Data Storytelling, and Stakeholder Communication, which are crucial for a Data Analyst role. Their project descriptions reflect the application of these skills in identifying insights and presenting them. The focus on learning agility and attention to detail suggests a good operational fit for roles requiring continuous learning and precision.