Data Analyst with less than a year in Data Operations & Process Management
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Detail-oriented and analytical professional with a background in Process Management and Data Operations, now transitioning into the field of Data Analytics. Skilled in leveraging tools such as Excel, Power BI, SQL, and Python to derive insights and support data-driven decision making. Eager to join a forward-thinking organization where I can apply my data analytics skills to drive insights and contribute to informed business decisions.
Bharathiar University
M.Com · Accounting
May 31, 2021 – April 23, 2023
Barclays Shared Services
Process Associate
February 1, 2018 – September 23, 2018
Chennai, Tamil Nadu, India
Consumer Purchasing Patterns;An Analysis of Shopping Behavior
January 1, 2026 – June 1, 2026
Analyzed a dataset of 3,900 shoppers using Pandas and NumPy to identify revenue-driving product categories and seasonal shopping trends, ensuring data integrity by handling missing values and duplicates. Evaluated demographic purchasing patterns and customer satisfaction metrics, such as review ratings, across different genders and age groups to derive actionable business intelligence for targeted marketing. Identified preferred payment methods (e.g., Venmo, PayPal) and frequency of purchases to provide strategic recommendations for streamlining checkout processes and enhancing subscription program benefits.
View ProjectRetail Sales Analytics Dashboard- Blinkit (Power BI)
January 1, 2026 – June 1, 2026
Designed and implemented an interactive Power BI dashboard to analyze 1M+ Total sales across key retail dimensions. Identified top performing products and locations to guide data-driven sales and inventory strategies. Visualized core KPIs including average sales and customer ratings for performance monitoring.
View ProjectHealthcare Analysis Dashboard (Excel)
January 1, 2026 – June 1, 2026
Designed and build a dynamic dashboard analyzing patient health data and healthcare costs. Utilized advanced Excel features (charts, formulas) to visualize correlations between factors like smoking status, weight, and the prevalence of Diabetes/Prediabetes
View ProjectMarketing Campaign Performance Insights-Python DA
January 1, 2026 – June 1, 2026
Performed comprehensive EDA on a dataset of over 22,000 campaign records using Pandas and NumPy to identify key performance drivers, such as the relationship between acquisition costs and ROI. Developed interactive visualizations using Seaborn and Matplotlib, including heatmaps for engagement-conversion correlations and multi-dimensional bar charts to compare channel effectiveness across 10 global locations. Analyzed campaign metrics across 5 customer segments (e.g., Tech Enthusiasts, Foodies) to determine high-performing channels like Facebook and Google Ads, providing data-driven insights to improve overall conversion rates.
View ProjectE-Commerce Customer Churn Analysis-MySQL
January 1, 2026 – June 1, 2026
Streamlined a dataset of over 5,000 customers by imputing missing values (Mean/Mode) for key metrics like tenure and order count, handling outliers, and standardizing categorical variables using SQL. Leveraged advanced SQL techniques, including Window Functions, CTEs, and Subqueries, to identify critical churn drivers such as high complaint rates and distance from warehouses. Developed a customer segmentation model based on distance and churn status, providing data-driven recommendations to improve retention for the 17% of customers identified as churned.
View ProjectAI Driven Data Analytics
Illinois Tech, US.
June 1, 2026 – Present
AI Driven Data Analytics
Entri, NSDC.
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, covering consumer purchasing, retail sales, healthcare, marketing campaigns, and e-commerce churn, indicates a broad interest in applying data analytics across different domains. This adaptability and willingness to tackle varied challenges suggest a good cultural fit for dynamic, data-driven environments. The certifications in 'AI Driven Data Analytics' also show a proactive approach to continuous learning and staying current with industry trends.
Soft Skills & Operational Fit
The candidate highlights communication, teamwork, attention to detail, and adaptability as soft skills. These are crucial for a Data Analyst role, especially in collaborating with stakeholders and presenting insights. The project descriptions indicate an operational fit through problem-solving and data-driven decision-making.