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Data Analyst with less than a year in Power BI, Python, and SQL for actionable insights.
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Assessing your cultural and operational fit
Results-driven Data Analyst with hands-on experience in Power BI, Tableau, Advanced Excel, Python, and SQL. Proven ability to transform large datasets into actionable business insights through interactive dashboards, statistical analysis, and data visualization. I Completed B.Tech in Computer Science (AI & ML), with strong expertise in EDA, data cleaning, KPI reporting, and stakeholder-ready reporting. Seeking to leverage analytical and BI skills to drive data-driven decision-making in a fast-paced analytics environment.
Vaagdevi Engineering College, Warangal
B.Tech · Computer Science & Engineering (AI & ML)
August 1, 2022 – June 30, 2026
Sales and Profit Analysis Dashboard
June 1, 2026 – Present
Developed a multi-dimensional Power BI dashboard to analyze sales, profit, quantity sold, discounts, and order trends - enabling period-over-period performance comparisons (daily, monthly, quarterly, yearly). Identified top 5 and bottom 5 products by sales, profit, and quantity sold to guide product strategy and inventory decisions. Built dynamic filters and interactive visuals exploring KPIs by product, customer segment, promotion category, city, and date range. Delivered insights on discount impact, seasonal demand patterns, and city-wise revenue distribution to support executive decision-making.
Business Analytics & Executive Dashboard
June 1, 2026 – Present
Built an end-to-end Excel analytics solution using transactional data to analyze revenue, expenses, profit margins, and customer behavior across multiple business dimensions. Designed 8+ pivot tables evaluating performance by region, product line, department, payment method, and customer segment; built comparison reports to identify high-profit products and cost-efficient departments. Developed an interactive executive dashboard featuring KPI summary cards, revenue trend charts, and profitability insights, reducing manual reporting time significantly. Delivered actionable insights on top revenue-generating products, high-value payment methods, and regional demand patterns.
View ProjectCustomer Churn Prediction Model
June 1, 2026 – Present
Built an end-to-end machine learning pipeline to predict customer churn for a telecom dataset of 7,043 records using Python (Pandas, Scikit-Learn, Seaborn), achieving 82% model accuracy with a Random Forest classifier. Performed comprehensive EDA, feature engineering, and label encoding on 21 features; applied SMOTE to handle class imbalance and improve minority class recall by 18%. Evaluated models using confusion matrix, ROC-AUC (0.87), precision-recall curves; identified top churn drivers - contract type, tenure, and monthly charges - enabling targeted retention strategies. Visualized churn patterns using Matplotlib and Seaborn; delivered a feature importance report showing contract type as the strongest predictor with 34% contribution.
Cultural Fit Analysis
The candidate's projects are all academic, which is typical for someone with an experience level of 0. The projects align well with a Data Analyst role, showcasing diversity in tools (Power BI, Excel, Python ML) and analytical approaches. However, the lack of professional experience means cultural fit in a corporate environment is yet to be proven.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to translate data into actionable business insights and a focus on delivering stakeholder-ready reports. The academic nature of projects suggests a learning-oriented individual, but real-world operational experience and collaboration skills are not explicitly demonstrated.