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Data Analyst with 1+ years in Data Analysis & Business Intelligence
Aspiring Data Analyst with hands-on experience in data analysis, visualization, and business intelligence using SQL, Python, Power BI, Tableau, and Excel. Skilled in transforming raw data into actionable insights through dashboards, predictive analysis, and data-driven problem solving. Completed multiple real-world projects in e-commerce, healthcare, finance, and manufacturing analytics. Strong understanding of business operations combined with analytical thinking, data cleaning, and visualization skills to support strategic decision-making and improve operational efficiency.
Ivy Professional School For Business - Kolkata
Data Analytics Program, Advanced Excel, MySQL, Power BI, Tableau, Python Programming, Advanced Python, Excel VBA, Foundational GenAI · Data Analytics
August 1, 2026 – March 1, 2026
Calcutta University - Kolkata
Bachelor of Commerce, Finance and Accounts · Finance and Accounts
August 1, 2012 – April 1, 2012
Premier Maruti NEXA Service Center
Cashier
August 1, 2023 – September 1, 2024
Kolkata, West Bengal, India
Salagram Power and Steel Ltd
Operations Support
April 1, 2023 – August 1, 2023
Kolkata, West Bengal, India
Retail Business Owner
Apparel and Cosmetics Shop
January 1, 2020 – December 1, 2021
Kolkata, West Bengal, India
Butterfly Collection
Operations and Sales
January 1, 2018 – December 1, 2020
Kolkata, West Bengal, India
Shagun Bangles
Artificial Ornaments Manufacturing Unit Management
January 1, 2016 – December 1, 2018
Kolkata, West Bengal, India
Butterfly Collection
Operations and Sales
January 1, 2012 – December 1, 2016
Kolkata, West Bengal, India
E-commerce Delivery Performance & Customer Satisfaction Analysis
June 17, 2026 – Present
Analyzed 2 datasets (orders + feedback) using MySQL and Microsoft Excel, uncovering ~29.5 min avg delivery time consistency across all categories and stable service performance. Identified refund concentration on Blinkit (highest among platforms) and tracked delivery delay reduction from 14.26% -> 13.23% (-7.2% improvement), indicating improved logistics efficiency. Built Excel dashboards to monitor monthly order trends and cumulative growth, revealing continuous increase in total orders despite monthly fluctuations and peak demand variability.
Hospital Emergency Room Analytics Dashboard
June 17, 2026 – Present
Identified critical bottlenecks with ~35 min avg wait time and low satisfaction (~5/10), enabling targeted process improvements to enhance patient experience and reduce delays. Uncovered peak demand patterns (Mon: 1377 patients; peak hours: 11 AM, 7 PM, 11 PM), driving data-backed staffing optimization to prevent overcrowding and improve service efficiency. Revealed inefficient resource utilization (5400+ non-referrals, ~50% admissions), supporting better triage decisions and optimized department allocation.
Electric Vehicle Data Analysis Dashboard
June 17, 2026 – Present
Enabled market trend identification across 150K+ EV records, supporting data-driven decisions on EV adoption strategy and infrastructure planning. Drove brand performance insights (Tesla ~52% share), helping stakeholders benchmark competitors and optimize product positioning. Improved regional and temporal decision-making by uncovering state-wise demand patterns and post-2020 growth surge, supporting targeted expansion and policy planning.
Smart Ai Hospital Finder
June 17, 2026 – Present
Built an AI-powered recommendation tool using Streamlit and Google Generative AI, enabling real-time hospital suggestions across 10 major Indian cities for 9 critical conditions. Automated hospital discovery process using LLM-based prompt generation, reducing manual search effort and improving decision speed for critical healthcare needs. Designed an interactive UI with dynamic inputs (condition + city), enhancing accessibility and enabling user-driven, personalized healthcare insights.
Financial Loan Risk Analysis & Prediction
June 17, 2026 – Present
Processed 38,576 loan records, identifying 13.8% defaults (5,333 loans) and 86.2% performing loans (33,243 loans). Evaluated $435.8M funded vs $473.1M received, generating ~$37.3M net profit. Built ML model achieving 0.697 ROC-AUC, 0.696 F1-score, and 64% accuracy on 11,244 test samples. Reduced feature space from 24 -> 16 variables, improving model efficiency while maintaining predictive performance. Identified statistically significant predictors (8 continuous + 5 categorical variables, p < 0.05) for default risk modeling.
Manufacturing Defect Prediction
June 17, 2026 – Present
Consolidated 12,204 records from 8 data sources, reducing duplicates by ~0.65% (80 rows removed) and creating 38-feature dataset. Built ML model achieving 0.986 ROC-AUC and ~95% accuracy on 3,662 test samples, with 0.95 weighted F1-score. Achieved 95% defect recall (935/984 defects detected) by optimizing threshold (0.3), significantly reducing defect leakage. Improved prediction alignment with 3,418 correct predictions vs 244 errors (~93.3% accuracy at tuned threshold). Engineered 54 predictive features from 38 variables, enhancing model capability for real-time defect detection.
Data Analytics And Visualization Certification
Ivy Professional School
March 1, 2026 – Present
Gen-AI Foundation Certification Program
Ivy Professional School
March 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, spanning finance, manufacturing, e-commerce, and healthcare, demonstrates adaptability and a broad interest in applying data analysis across different industries. While their professional experience prior to data analytics is primarily in operational and retail roles, the transition to data analytics through a dedicated program and multiple projects indicates a strong drive for career change and learning. The inclusion of a GenAI project suggests an openness to new technologies and innovation. The candidate's background in business operations could provide a practical perspective to data analysis, which can be valuable for understanding business context.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to identify bottlenecks, optimize processes, and improve efficiency, which suggests a good operational fit. Their past roles as a retail business owner and in operations support also imply practical problem-solving and management skills. The focus on quantifiable results in projects (e.g., 'reduced feature space', 'achieved 95% defect recall') suggests a results-oriented approach.