Sentiment Analysis
Classified customer feedback as positive, negative, or neutral using Logistic Regression and Random Forest, achieving 82% accuracy.
1roles
30skills
1education
1credentials
About
Results-driven Operation & Data Analyst with 1 year of experience in business operations, data analysis, machine learning, and business intelligence. Skilled at deriving actionable insights from complex datasets to support business growth and strategic decision-making.
Experience
Operation & Data Analyst
Dr. Sheth's
May 2025 – May 2026 · 1 Year · Mumbai, Maharashtra
Managed day-to-day operational tasks and cross-department coordination for clinic workflow. Developed daily and weekly MIS reports, stock and inventory reports, and performance reports. Built interactive dashboards using Looker Studio and Excel for real-time visibility into operational and business performance metrics. Tracked and consolidated departmental data to ensure accurate, timely reporting aligned with business objectives and KPIs. Prepared finance reports covering revenue, expenses, and profit margins. Used CRM and payment software to manage patient records, interactions, and transactions. Created service costing models for medical treatments and services to support pricing and profitability analysis. Performed exploratory data analysis on financial and operational data, identified high-performing services, and delivered insights to support business growth.
Education
Mahatma Jyotiba Phule Rohilkhand University
Bachelor of Arts, History
2021 – 2024
Skills
PythonSQLLogistic RegressionRandom ForestK-MeansTime SeriesPower BITableauLooker StudioExcelVLOOKUPHLOOKUPSUMIFSUMIFSCOUNTIFCOUNTIFSPivot TablesGoogle SheetsJupyterMySQLCRM softwarePayment softwareData CleaningExploratory Data AnalysisFeature EngineeringInventory & Stock ManagementMIS ReportingFinance ReportingService CostingDashboard Building
Projects
Weather Prediction
Developed a time series forecasting model to predict temperature and rainfall trends using Logistic Regression.
Customer Segmentation
Applied K-means clustering to segment customers by purchasing behavior and improved customer retention by 20%.
Bank Loan Approval Prediction
Led a team of 10 to predict loan approvals with an optimized classification machine learning model, improving accuracy by 18%.