Summary
Overview
Work History
Education
Skills
Websites
Timeline
Generic

Koteswararao G

Wilmington,DE

Summary

Junior Data Analyst with 4+ years of experience in data analysis, data cleaning, data validation, and data visualization using SQL, Power BI, Tableau, Excel, DAX, and Python. Skilled in building interactive dashboards, automating reports, and performing data profiling to improve data accuracy, and reduce reporting errors by 30%. Proficient in ETL processes, dashboard migration, and translating business requirements into BI solutions. Experienced in working with cross-functional teams to deliver KPI-driven insights, accelerate reporting cycles by 25%, and support marketing A/B testing analysis for improved customer engagement and conversion rates.

Overview

6
6
years of professional experience

Work History

Junior Data Analyst

JP Morgan Chase
04.2025 - Current
  • Enhanced credit risk modeling using historical data analysis, reducing high-risk credit approvals by 18% and minimizing default rates through advanced SQL and Python analytics.
  • Optimized ETL pipelines handling millions of daily transactions with tools like Apache Airflow, Talent, and SQL, cutting data processing time by 35% and boosting reporting efficiency.
  • Developed executive-level dashboards in Tableau to provide real-time customer spending insights, enabling data-driven decision-making for senior management.
  • Implemented fraud detection analytics by analyzing transaction patterns with machine learning and Python, reducing chargeback fraud losses by 25%.
  • Improved customer retention by 12% through enhancement of churn prediction models using Scipio-learn and predictive analytics techniques.
  • Automated monthly reconciliation reports leveraging SQL workflows and Python scripting, reducing reporting time by 40% and improving data consistency.
  • Advanced marketing segmentation and personalization models with Python and Power BI, increasing customer engagement by 22%.
  • Conducted comprehensive A/B testing and product feature analysis using Excel, Python, and Power BI, optimizing customer offerings based on feedback and metrics.
  • Refined financial forecasting models incorporating external economic indicators using Python, time-series forecasting, and regression analysis to enhance business planning.
  • Improved reward program tracking tools with Tableau and SQL, driving a 35% increase in incentive redemptions through detailed analytics.
  • Led migration from on-premises SQL servers to Google BigQuery, improving data warehouse scalability, performance, and cost-efficiency.
  • Redesigned business intelligence workflows using Tableau, Power BI, and SQL to streamline report generation and reduce manual effort by 50%.
  • Created KPI tracking dashboards to deliver real-time financial insights into revenue and cost optimization, leveraging Power BI and SQL.
  • Built an NLP-driven customer sentiment analysis pipeline using Python (NLTK, spay), extracting insights from feedback and identifying areas for product improvement.
  • Designed a recommendation engine using machine learning and Python, personalizing credit card offers and increasing conversion rates.
  • Integrated external market data into financial models using Python and SQL, enhancing predictive analytics on consumer spending trends.
  • Environment: SQL, Power BI, Excel, BigQuery, DAX, Git, Tableau, Google Cloud, Confluence, Python, Google Big Query, Apache Airflow, Tableau, Power BI, Jupiter Notebooks, Pandas, Nubby, GCP (Cloud Storage, Cloud Composer, Dataflow, Pub/Sub), Looker, Vertex AI, Git, GitHub, Google Data Studio, Big Query ML, Google Cloud Functions, Apache Beam, Google Analytics, Segment

Junior Data Analyst

Genpact
02.2021 - 12.2022
  • Company Overview: India
  • Developed and automated inventory optimization and demand forecasting models using Python, SQL, and time-series analysis, reducing overstock and food waste by 18%, saving $3M annually.
  • Designed and maintained Power BI dashboards for real-time KPI monitoring, improving store-level decision-making efficiency by 25%.
  • Built and refined machine learning models for dynamic pricing, customer segmentation, and churn prediction with Scipio-learn and Pandas, increasing revenue margins and customer retention.
  • Enhanced loyalty program analytics dashboards in Power BI, driving a 30% increase in incentive redemption through consumer behavior insights.
  • Integrated multi-source supplier and logistics data using Azure Data Factory and T-SQL, improving vendor performance tracking and decreasing delivery delays by 20%.
  • Created store performance rating frameworks using DAX and Power BI, enabling targeted interventions and boosting sales by 10%.
  • Implemented fraud detection systems leveraging Python and anomaly detection algorithms, reducing fraudulent store transactions by 22%.
  • Executed A/B testing for store layout and marketing campaigns with Excel and Power BI, increasing foot traffic efficiency by 17%.
  • Automated complex reporting workflows using Python, SQL, and Power Query, cutting manual effort and accelerating report delivery by 30%.
  • Analyzed mobile payment adoption and transaction performance using Google Analytics and Power BI, optimizing digital wallet usage.
  • Optimized supply chain logistics and delivery routing using Python and data visualization tools, reducing distribution center costs by 8%.
  • Developed targeted promotional strategies based on transactional data analysis using SQL, Python, and Azure Synapse, increasing repeat customer business by 15%.
  • Built pricing elasticity and recommendation models using regression analysis and machine learning techniques, enabling strategic pricing decisions.
  • Collaborated with cross-functional teams via Azure DevOps, SharePoint, and Confluence, aligning analytics initiatives with business goals.
  • Maintained and published dashboards, reports, and documentation in Power BI, Excel, and SharePoint, ensuring data accuracy and team collaboration.
  • India
  • Environment: Power BI, SQL, Excel, Azure Synapse, DAX, Tableau

Data Analyst

Altos Santee
07.2019 - 01.2021
  • Company Overview: India
  • Cleaned and transformed geospatial datasets using Python and SQL, enabling real-time monitoring dashboards for asset tracking.
  • Automated weekly data reports using Excel macros and Power Query, reducing delivery time and manual input errors.
  • Assisted in implementing predictive maintenance models using historical sensor data and trend analysis.
  • India
  • Environment: Power BI, SQL, Excel, Python, Azure, ArcGIS

Education

Master of Information Systems - New Castle, DE

Wilmington University
New Castle, DE
08.2025

Skills

Programming Languages: Python, SQL , R , SAS
Data Visualization: Tableau , Power BI , Looker
Machine Learning: Scikit-learn , TensorFlow , XGBoost , NLP , Anomaly Detection
Big Data Technologies: Hadoop , Spark , Google Big Query , Databricks
Databases: MySQL , PostgreSQL , Snowflake , MongoDB , Redshift , Oracle SQL
Cloud Platforms: AWS , Azure , Google Cloud Platform
ETL & Data Pipelines: Apache Airflow , Alteryx , Talend
Statistical & Predictive Analysis: Hypothesis Testing , Regression Analysis , Time Series Forecasting , Bayesian Modeling , A/B Testing
Tools & Collaboration: Git , GitHub Confluence , SharePoint , Jupyter Notebooks , Excel , Google Workspace

Timeline

Junior Data Analyst

JP Morgan Chase
04.2025 - Current

Junior Data Analyst

Genpact
02.2021 - 12.2022

Data Analyst

Altos Santee
07.2019 - 01.2021

Master of Information Systems - New Castle, DE

Wilmington University

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