Data Analyst with 3+ years in Data Analysis & Business Intelligence
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Data Analyst with 3.1 years of experience in collecting, cleaning, analyzing, and visualizing large datasets to support data-driven business decisions. Strong expertise in Python, SQL, Excel, and Power BI, including advanced SQL concepts (CTEs, window functions) and dashboard development using DAX. Proven ability to translate business requirements into actionable insights, automate reporting workflows, and collaborate with cross-functional stakeholders to improve operational efficiency and KPI tracking.
University of Pune
Bachelor of Engineering · Computer Science
N/A – June 30, 2022
Mphasis
Data Analyst
December 1, 2022 – January 31, 2026
India
Telco Customer Churn Analysis
January 1, 2024 – December 31, 2024
Led data extraction, transformation, and aggregation using advanced SQL (multi-table joins, CTEs, subqueries, window functions). Conducted end-to-end data cleaning, preprocessing, and exploratory data analysis on a customer churn dataset. Handled missing values, encoded categorical variables, and normalized data using Pandas and NumPy. Built EDA visualizations using Matplotlib and Seaborn to identify churn patterns and customer behavior trends. Created correlation matrices and statistical insights to identify key churn drivers impacting retention. Designed and implemented an ETL pipeline to automate data preparation and reporting. Outcome: Automated reporting for 100K+ customer records. Reduced manual analysis effort by 50%. Provided actionable insights to support customer retention strategies.
Sales Performance & KPI Dashboard
January 1, 2023 – December 31, 2023
Applied SQL DDL and DML operations to create, modify, and manage sales tables, implemented constraints (PRIMARY KEY, FOREIGN KEY, NOT NULL, UNIQUE) to ensure data integrity. Analyzed 12 months of sales and revenue data to track monthly, quarterly, and product-level performance trends. Built Power BI dashboards with DAX measures to monitor KPIs such as revenue growth, conversion rate, and regional performance. Used SQL queries to aggregate and validate sales data from multiple sources. Outcome: Enabled leadership to track KPIs in real time. Improved visibility into sales performance and trend analysis.
Cultural Fit Analysis
The candidate's projects demonstrate a practical, results-oriented approach, focusing on business impact (e.g., reduced manual effort, actionable insights, real-time KPI tracking). The experience at Mphasis and personal projects show a breadth of skills relevant to data analysis, indicating adaptability and a willingness to tackle diverse data challenges. The mention of stakeholder communication and team collaboration suggests a team-player mindset, which is positive for cultural integration.
Soft Skills & Operational Fit
The candidate highlights problem-solving, analytical thinking, stakeholder communication, attention to detail, and team collaboration. These align well with the operational demands of a Data Analyst role, which often requires clear communication of insights and collaborative problem-solving. The experience in automating reports and supporting multiple stakeholders indicates a good operational fit for efficiency and responsiveness.