Data Analyst with 1+ years in Python, SQL & Power BI
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Data Analyst with 1+ year experience analyzing 130K+ records using Python, SQL, Power BI, and Excel to support business decisions. Developed ETL pipelines, automated reporting workflows, and interactive dashboards, reducing manual effort by up to 30%. Delivered analytics, machine learning, and NLP solutions across insurance, retail, and finance domains, generating actionable business insights.
Chebrolu Engineering college
Bachelor of Technology · CSE(AI &ML)
N/A – June 30, 2026
BlackBucks
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SmartInternz
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DVSoft
Python Developer
December 1, 2024 – April 1, 2025
India
Insurance Risk & Claims Analysis
June 1, 2026 – Present
Analyzed 30K+ insurance claim records to identify high-risk customer segments contributing to 20% higher claim costs and support risk reduction initiatives. Evaluated claim frequency and severity trends, revealing that private vehicle usage accounted for nearly 80% of total claims and highlighting opportunities for premium optimization. Developed an interactive Power BI dashboard with DAX KPIs and drill-through analysis, reducing reporting effort by 30% and enabling faster risk-based decision-making.
Swiggy Data Warehouse & Analytics Project
June 1, 2026 – Present
Designed a Star Schema data warehouse with 5 dimension tables and a fact table, transforming 30K+ food delivery records into an analytics-ready structure for scalable reporting. Developed a SQL-based data quality pipeline using CTEs and ROW_NUMBER(), validating 30K+ records and eliminating duplicate entries to ensure accurate business analysis. Built 15+ analytical SQL queries to analyze revenue, customer ratings, cuisine performance, restaurant trends, and geographic demand patterns, enabling data-driven pricing and operational decisions.
Credit Card Fraud Detection & Real-Time Risk Analysis
June 1, 2026 – Present
Developed Random Forest and Logistic Regression models on 30K+ transaction records, achieving 97% classification accuracy for fraud detection. Applied SMOTE, feature scaling, and preprocessing techniques, improving minority-class recall by 25% and enhancing fraud identification performance. Built an interactive Streamlit application with 5+ analytical visualizations and real-time transaction prediction capabilities for fraud risk assessment.
Machine Learning Using Python
NPTEL (Elite Certification)
June 1, 2026 – Present
Data Visualization: Empowering Business with Effective Insights
Tata Group (Forage)
June 1, 2026 – Present
Professional Certificate Program in AI and Data Science
PwC Academy & UpGrad
June 1, 2026 – Present
Generative AI for Data Science and AI Practitioners
Microsoft & UpGrad
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity (insurance, food delivery, finance) and exposure to various data analysis and machine learning tasks indicate a broad interest and adaptability, which can be beneficial for cultural fit in dynamic environments. The internships and certifications suggest a strong drive for continuous learning and professional development. The target role of 'Data Analyst' aligns well with the candidate's demonstrated skills in data analysis, visualization, and SQL, though the ML/NLP aspects lean towards a Data Scientist profile.
Soft Skills & Operational Fit
The candidate's project descriptions and experience highlight a results-oriented approach, with quantifiable achievements in reducing effort and improving efficiency. The diverse project portfolio suggests adaptability and a proactive learning attitude. However, without direct interview data, specific soft skills like teamwork, leadership, or conflict resolution cannot be fully assessed.