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Data Analyst with 6+ years in Data Analysis, SQL & Power BI
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Detail-oriented and results-driven Data Analyst with strong expertise in data analysis, SQL, Python, Power BI, Tableau, and business intelligence solutions. Skilled in transforming raw datasets into meaningful insights through data cleaning, visualization, exploratory data analysis (EDA), and dashboard development. Experienced in analyzing customer behavior, churn prediction, shopping trends, and business performance metrics to support strategic decision-making. Proficient in creating automated reports, KPI dashboards, and predictive analytics models to improve operational efficiency and business growth.
Swami Ramanand Teerth Marathwada University (SRTMUN)
Bachelor of Engineering (B.E.) · Electronics
N/A – June 30, 2020
Customer Shopping Trend Behavior Analysis
June 1, 2020 – June 1, 2026
Designed and implemented a Customer Shopping Trend Behavior Analysis system to analyze purchasing patterns, customer preferences, and seasonal shopping trends using retail transactional data. Used Python, SQL, and Power BI to process large datasets and visualize customer buying behavior across different product categories and demographics. Identified high-performing products, peak shopping periods, and customer segments to support targeted marketing campaigns and sales optimization strategies. Key Responsibilities: • Analyzed customer transaction data using Python and SQL • Developed interactive Power BI dashboards for sales and shopping trend analysis • Conducted customer segmentation and behavioral analysis • Identified top-selling products and seasonal purchase patterns • Performed data preprocessing and visualization for accurate reporting • Generated actionable business insights to improve sales performance
Customer Churn Analysis
June 1, 2020 – June 1, 2026
Developed a comprehensive Customer Churn Analysis project to identify customers likely to discontinue services using customer behavioral and transactional datasets. Performed extensive data preprocessing, exploratory data analysis (EDA), and feature engineering to identify critical churn indicators such as customer tenure, subscription patterns, and support interactions. Utilized Python, SQL, Power BI, and Tableau to analyze customer behavior and create dynamic dashboards for churn monitoring and retention tracking. Applied predictive analytics techniques to improve customer retention strategies and generate actionable business insights. Key Responsibilities: • Performed data cleaning, transformation, and validation on customer datasets • Conducted EDA and statistical analysis to identify churn patterns and KPIs • Developed interactive Power BI dashboards for churn tracking and reporting • Used SQL queries to extract, filter, and analyze customer data efficiently • Generated business insights to support customer retention strategies • Created visual reports and dashboards for stakeholder presentations
Cultural Fit Analysis
The candidate's projects demonstrate a proactive approach to problem-solving and a clear understanding of business objectives (e.g., improving sales, customer retention). The breadth of tools and techniques used (Python, SQL, Power BI, Tableau, advanced Excel, statistical methods) indicates adaptability and a willingness to learn and apply diverse solutions. The focus on delivering actionable insights suggests a results-oriented mindset that would fit well in a data-driven culture.
Soft Skills & Operational Fit
The candidate's project descriptions highlight a detail-oriented and results-driven approach. The focus on generating actionable business insights and supporting strategic decision-making indicates a strong operational fit for roles requiring practical application of data analysis. The ability to create visual reports and dashboards suggests good communication of findings.