Data Analyst - SQL, Python, Tableau, Power BI Expert

Chandu Kurre

USA 713-***-**** **************@*****.***

Summary

Data Analyst with 3+ years of experience analyzing operational data, developing reports, and creating Tableau dashboards to drive process improvements. Skilled in SQL, Python, and Excel to aggregate and visualize complex datasets, identify trends, and recommend actionable solutions. Proven track record supporting cross-functional teams, ensuring data accuracy and confidentiality, and preparing clear presentations and documentation for departmental needs.

Education

University of North Texas, Denton, Texas, USA Aug 2023 - May 2025 Master of Science, Data Science

Amrita School of Engineering, Bengaluru, India Jun 2019 - Jul 2023 Bachelor of Technology, Electronics and Communication Engineering Professional Experience

Stripe Oct 2024 - Present

Data Analyst Remote, USA

• Collaborated with Product, Data Science, and CX teams in Agile sprints, multitasking across concurrent projects, to define KPIs and gather requirements for customer retention and churn analysis across Stripe's core payment services.

• Wrote efficient SQL queries using window functions and CTEs in PostgreSQL and managed database schemas to optimize performance while analyzing large-scale transactional and customer behavior data, supporting data-driven decision-making.

• Performed exploratory, cohort, and segmentation analysis on user lifecycle metrics such as tenure, region, and business type, identifying a 22% churn spike in SMB users through retention curve insights.

• Analyzed user onboarding patterns, support interactions, and product usage using Python (NumPy, Pandas, SciPy, Seaborn), revealing that users with more than three support interactions in the first month had a 31% higher churn rate.

• Ensured data accuracy and consistency through routine validation and profiling in Microsoft Excel and SQL, contributing to 99.5% data integrity across key churn datasets.

• Built interactive Power BI dashboards with drill-through filters, dynamic churn risk indicators, and KPI tracking using DAX, increasing dashboard adoption by CX teams by 40% and enabling more proactive retention strategies. Dell Technologies Jul 2021 - Aug 2023

Data Analyst Bengaluru, India

• Collected sales data from SAP and external sources for dynamic forecasting and used Microsoft Excel and PowerPoint for requirement sessions, collaborating with Sales, Finance, and Product teams via Agile sprints to map regional sales trends across Enterprise, Government, and SMB sectors.

• Designed optimized SQL queries on Azure Synapse to extract and transform of structured data from SAP HANA and Snowflake; improved ETL pipeline efficiency by 28%, reducing daily data refresh time.

• Performed time series analysis using ARIMA and exponential smoothing to forecast sales trends through detailed data analysis, identifying key seasonal cycles impacting demand across regions, enabling 18% more accurate quarterly forecasting aligned with macroeconomic indicators.

• Utilized Python with NumPy and Pandas to preprocess datasets, handle missing values, and engineer features. Automated outlier detection reduced manual QA hours by 22% and ensured cleaner inputs for modeling and visualizations.

• Implemented regression analysis in R using the lm method to understand the relationship between GDP growth and Dell's B2B device sales. Found a 0.82 correlation, influencing executive strategy in semi-urban market penetration.

• Validated data pipelines using Azure Data Factory and Azure Data lake for ETL processing. Developed logic for schema validation, improving data accuracy by 31% and reducing cross-team data quality escalations significantly.

• Built interactive Tableau dashboards using LOD expressions for segment-level sales variance. Integrated drill-down filters and dynamic YoY change graphs, leading to 25% increase in executive engagement during monthly forecast reviews. Dell Technologies Jan 2021 - Jun 2021

Jr. Data Analyst Bengaluru, India

• Assisted in collecting and cleaning sales data from SAP and IDC sources. Participated in Agile meetings with finance and product teams to understand forecasting requirements and support initial data modeling tasks.

• Wrote basic SQL queries in Azure Synapse to extract sales records. Helped maintain ETL workflows, improving data refresh efficiency by 15% across regional datasets used in forecasting dashboards.

• Supported Tableau dashboard creation by preparing structured datasets and applying LOD calculations. Enabled filter functionality and trend lines that improved visibility for product-wise sales performance across India's SMB segment. Technical Skills

• Languages & Programming: SQL, PostgreSQL, Azure Synapse, Python, NumPy, Pandas, SciPy, Seaborn, R

• Data Engineering & ETL Tools: Azure Data Factory, Azure Data Lake, SAP HANA, Snowflake, E, Deep Learning, Database Management

• Statistical & Analytical Techniques: Time Series Analysis, ARIMA, Exponential Smoothing, Cohort Analysis, Regression Modeling, R lm, Segmentation, Outlier Detection, Data Profiling & Validation, Data Analysis

• Business Intelligence & Visualization: Power BI, DAX, Dynamic Filters, KPI Indicators, Tableau, LOD Expressions, YoY Analysis, Drill-downs, Business Intelligence, Artificial Intelligence

• Data Sources & Systems: SAP, IDC, Stripe internal CX & transactional data

• Methodologies: Agile, KPI Definition, Forecasting, Retention & Churn Analysis, Onboarding & Lifecycle Metrics, Multitasking

• Productivity Tools: Microsoft Office, Microsoft Excel

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