Karunakar Velpuri
Data Analyst • Chicago, IL • k*****************@gmail.com • +17******346 • drivetube.ai/•••••
Professional Summary
Data Analyst with 3+ years of experience translating large-scale operational and transactional data into actionable business insights. Proficient in Python and SQL for analysis and pipeline development, and experienced building AWS-based ETL pipelines (S3, Redshift, EC2) and Power BI dashboards to support fraud detection and revenue analytics. Delivered machine-learning prototypes using scikit-learn and engineered features with Pandas to prioritize investigations and reduce manual effort. Built Text-to-SQL and LLM-powered assistants using retrieval-augmented generation to make analytics accessible to non-technical stakeholders. Comfortable defining KPIs, designing A/B tests, and partnering with product and operations teams to convert data signals into operational improvements.
Technical Skills
Programming Language: Python,SQL
Databases: PostgreSQL
Cloud Platforms: Amazon Web Services,S3,EC2
Version Control & Development Tools: Git,Jupyter Notebook
Data Engineering & Processing: Data Pipelines
Data Analysis & Visualization: A,Text-to-SQL,Power BI,Tableau,QuickSight
Machine Learning & AI: Anomaly Detection
AI/ML Frameworks & Libraries: scikit-learn
Generative AI & LLMs: LLMs
Vector Databases & RAG: RAG
Data Integration & ETL: ETL
Compliance & Governance: Risk Scoring
Work Experience
NTT Data, USA
Chicago, IL
Data Analyst
Aug 2025 – Present
Worked at NTT Data (IT services and consulting) on telecom and transactional data pipelines supporting fraud detection, revenue analytics and operational reporting.
Tech Stack: Python, SQL, AWS S3, Power BI
- Analyzed 100M+ telecom and transactional records using Python and SQL to identify fraud patterns, customer-behavior trends, and revenue-impacting anomalies.
- Built automated ETL pipelines on AWS S3 and Redshift to integrate, cleanse, and validate multi-source data, reducing manual reporting effort by 25%.
- Orchestrated EC2-based ingestion and transformation workflows to improve data availability across 40+ regions and accelerate downstream reporting.
- Designed and executed A/B tests using Python to measure feature impact and translated statistical results into product and operational recommendations.
- Developed Power BI dashboards and KPI frameworks for fraud and revenue monitoring to accelerate investigations and surface exceptions for business stakeholders.
- Implemented an anomaly-detection prototype and risk-scoring workflow to prioritize suspicious transactions and streamline triage for ops teams.
Maxgen Technologies, India
Telangana, India
Junior Data Analyst
Jan 2021 – Jul 2023
Worked on operational and transactional datasets to build ETL workflows, dashboards, and recurring reports supporting business and finance teams.
Tech Stack: SQL, Python, PostgreSQL, Power BI, Tableau, Amazon QuickSight, Excel
- Analyzed 50M+ operational records with SQL and Python to uncover data-quality issues, performance gaps, and opportunities for process improvement.
- Built ETL workflows to extract, transform, and load data into PostgreSQL, improving data consistency by 20%.
- Automated recurring data-preparation tasks using Python and Excel macros, saving approximately 15 hours per week in manual effort.
- Developed interactive dashboards with Power BI, Tableau, and Amazon QuickSight used by business teams for weekly operational reporting.
- Streamlined SQL reporting using window functions and query optimization to accelerate revenue-recovery analyses and monthly reconciliations.
- Performed exploratory analysis and statistical reporting to identify anomalies and support data-driven recommendations to stakeholders.
Projects
Fraud Detection & Risk Scoring Model
Tools Used: Python, Pandas, Scikit-learn, Anomaly Detection, Risk Scoring
- Developed a machine-learning fraud detection prototype using Pandas for feature engineering and scikit-learn for classification to surface high-risk transactions.
- Engineered transaction-level features and implemented a risk-scoring pipeline to prioritize suspicious activities and improve investigator efficiency.
Text-to-SQL AI Assistant Using LLMs & RAG
Tools Used: Python, LLMs, RAG, Text-to-SQL, Git, Jupyter Notebook
- Built an AI assistant that converts natural-language business questions into executable SQL using LLMs and retrieval-augmented generation for schema-aware prompts.
- Implemented retrieval, prompt engineering, and notebook-based tooling, and versioned code using Git to enable analysts to query databases via natural language.
Supply Chain Inventory Optimization Dashboard
Tools Used: Power BI, SQL, Excel
- Developed a Power BI dashboard to visualize inventory levels, reorder points, and supplier performance to support replenishment decisions.
- Applied SQL and Excel analyses to identify excess and slow-moving stock and recommend actionable replenishment and cost-saving measures.
Customer Churn Analysis for Telecom Services
Tools Used: Python, SQL, Power BI
- Analyzed telecom customer data to identify churn indicators across demographics, contract types, and billing behavior using Python and SQL.
- Built interactive Power BI dashboards to highlight high-risk segments and support targeted retention strategies.
Education
New Mexico State University
Masters in Data Analytics • New Mexico, USA • May 2025
St. Mary’s College
Bachelors in Computer Science • Telangana, India • Nov 2020
Certifications
Python for Data Science
Data Science with AI — Social Prachar
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