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Senior Data Analysis with 4+ years in Data Analysis & Visualization
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Results-driven Data Analyst with 4+ years of experience in transforming complex data into actionable business insights. Proficient in Python, Microsoft Power BI, Tableau, MySQL, and advanced Excel, with strong expertise in data analysis, visualization, and statistical modeling. Experienced in building scalable dashboards, optimizing SQL queries, and performing end-to-end data analysis to support strategic decision-making. Demonstrated ability to translate business requirements into data-driven solutions, improve reporting efficiency, and deliver impactful insights to stakeholders.
Shivaji University
Bachelor of Science · Statistics
August 1, 2016 – June 30, 2019
Maharastra state Board
Higher Secondary Schooling
June 1, 2015 – May 31, 2016
Maharastra state Board
Secondary Schooling
June 1, 2013 – May 31, 2014
Grihum Housing Finance Ltd
Data Analyst
March 1, 2025 – Present
India
Vionsys IT Solution Pvt Ltd
Jr Data Analyst
January 1, 2023 – February 1, 2025
India
Vionsys IT Solution Pvt Ltd
Trainee Data Analyst
January 1, 2021 – March 1, 2022
India
Business & Customer Data Analytics(Portfolio & Dashboards Development)
June 1, 2026 – June 1, 2026
Analyzed collection follow-up reports and created monthly cuts based on customer category, branch, region, LTV, and IRR. Built and enhanced dashboards in Microsoft Power BI and Excel to track delinquency, trendlines, and key metrics, including management and branch-level dashboards for performance monitoring and decision-making. Restructured CIBIL scrub data to identify high-risk accounts and key credit triggers. Monitored bounce trends, delinquency patterns, and portfolio exposure across segments. Developed data pipelines using Python and SQL to streamline reporting processes. Designed early warning systems (EWS) to flag potential defaulters. Performed cohort and segmentation analysis to understand customer behavior. Implemented Row-Level Security (RLS) in Microsoft Power BI to enable secure, role-based data access and ensure users view only relevant information. Conducted root cause analysis on performance trends and recommended corrective actions. Conducted exploratory data analysis (EDA) on franchise-level customer and sales data to identify regional purchasing patterns and market trends. Developed customer segmentation models using clustering techniques and demographic profiling to support targeted marketing and improve retention. Applied regression analysis and correlation studies to forecast sales, analyze purchasing behavior, and optimize inventory management. Performed detailed profit and loss analysis and raw costing assessments to identify inefficiencies and enhance franchise profitability. Built automated dashboards and visualizations to track key performance indicators (KPIs) and support faster, evidence-based decision-making. Used statistical hypothesis testing to validate business assumptions and improve marketing campaign effectiveness.
Franchise Performance Analysis
June 1, 2026 – June 1, 2026
Conducted exploratory data analysis (EDA) on franchise-level customer and sales data to identify regional purchasing patterns and market trends. Developed customer segmentation models using clustering techniques and demographic profiling to support targeted marketing and improve retention. Applied regression analysis and correlation studies to forecast sales, analyze purchasing behavior, and optimize inventory management. Performed detailed profit and loss analysis and raw costing assessments to identify inefficiencies and enhance franchise profitability. Built automated dashboards and visualizations to track key performance indicators (KPIs) and support faster, evidence-based decision-making. Used statistical hypothesis testing to validate business assumptions and improve marketing campaign effectiveness.
Supply Chain Efficiency Improvement
June 1, 2026 – June 1, 2026
Utilized MySQL on the in-house server to extract, filter, and organize warehouse data, helping identify delays, data gaps, and inconsistencies in daily operations. Built Power BI dashboards connected to the in-house server to visualize stock levels, order processing times, and warehouse KPIs for easy monitoring. Applied basic statistical analysis (mean, median, variance, frequency distribution) to study demand patterns and inventory movement across locations. Performed data cleaning, validation, and reconciliation to correct mismatches between system data and physical stock, improving data reliability. Conducted variance and trend analysis to detect unusual changes in stock usage, delivery times, and order volumes. Created clear data reports and visual insights that helped the team understand operational issues and improve daily warehouse activities.
Completed Workshop in Data Analytics using POWER BI
Unknown
June 1, 2026 – Present
Introduction to Python
Sololearn
June 1, 2026 – Present
Advanced Certification in Data Analytics with A grade
Edubridge india
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, spanning business/customer data analytics, franchise performance, and supply chain efficiency, indicates adaptability and a broad interest in applying data analysis across different domains. Their experience in both junior and senior data analyst roles, coupled with continuous learning (certifications), suggests a growth mindset. The skills align well with a Senior Data Analysis role, demonstrating a breadth of technical capabilities relevant to various business challenges.
Soft Skills & Operational Fit
The candidate demonstrates strong collaboration skills, working with cross-functional teams and external vendors. Their experience in data storytelling and delivering actionable insights suggests good communication of technical findings to business stakeholders. The focus on optimizing reporting efficiency and supporting data-driven decision-making aligns well with operational effectiveness.