Nagadeepthi Kodi

St Louis,MO

Summary

Results-driven Data Analyst with 4+ years of experience in transforming complex data into actionable business insights. Proficient in SQL, Python (Pandas, NumPy), and Excel for data extraction, analysis, and reporting. Experienced in building interactive dashboards using Power BI and Tableau to track KPIs and support strategic decision-making. Skilled in applying Generative AI (LLMs/OpenAI) to automate reporting, generate insights, and enhance analytical workflows. Strong knowledge of data cleaning, transformation, and ETL processes to ensure high-quality datasets. Proven ability to analyze large datasets, identify trends, and collaborate with cross-functional teams to deliver data-driven solutions that improve efficiency and business performance.

Overview

years of professional experience

Certification

Work History

Data Analyst - Gen AI

Kroger

Cincinnati, OH

03.2024 - Current

Analyzed sales data to identify trends and support decision-making processes.
Developed automated reports using SQL to enhance data accessibility for stakeholders.
Collaborated with cross-functional teams to improve inventory management accuracy.
Created data visualizations in Tableau to communicate insights effectively.
Built demand forecasting models using Python to improve inventory planning and reduce stockouts across retail stores
Analyzed pricing and promotion effectiveness to optimize discount strategies and maximize revenue
Developed SQL-based data pipelines to extract and process large volumes of POS (Point of Sale) data efficiently
Applied Generative AI tools to generate automated business insights, executive summaries, and anomaly explanations
Monitored supply chain and logistics data to identify bottlenecks and improve delivery timelines
Conducted A/B testing and performance analysis for marketing campaigns to improve customer conversion rates
Partnered with cross-functional teams to enhance data quality, streamline reporting processes, and support data-driven retail decisions

Jr. Data Analyst

Mphasis Limited

Pune, India

12.2021 - 09.2023

Analyzed data trends to support decision-making processes and enhance operational efficiency.
Developed and maintained dashboards using data visualization tools for reporting purposes.
Collaborated with cross-functional teams to identify data needs and improve analytical methods.
Conducted data quality assessments to ensure accuracy and reliability of datasets.
Analyzed large-scale datasets using SQL, Python (Pandas, NumPy), and Excel to derive actionable business insights and support decision-making
Designed and developed interactive dashboards using Power BI / Tableau to monitor KPIs and business performance
Utilized prompt engineering to generate SQL queries, automate documentation, and improve analysis efficiency
Automated recurring reports and workflows, reducing manual effort by 30–40% and improving accuracy
Performed data cleaning, transformation, and ETL processes to ensure high-quality, reliable datasets
Collaborated with cross-functional teams and stakeholders to deliver data-driven solutions and client-facing insights

Education

Master of Science - Information Technology And Management

Webster University

St. Louis, MO

12-2025

Bachelor of Science - Electronics And Communications Engineering

Mallareddy Engineering College

Hyderabad, India

05-2023

Skills

Data Analysis: SQL, Advanced Excel, Python, KPI Reporting, Data Cleaning, Data Validation, Data Modeling, Exploratory Data Analysis (EDA), Statistical Analysis, Business Intelligence Reporting, Data Governance

Data Visualization: Power BI, Tableau, Google Data Studio (Looker Studio), SSRS, Dashboard Development, Data Storytelling, Executive Reporting

Databases & Data Warehousing: SQL Server, PostgreSQL, Oracle, MySQL, Snowflake, MongoDB, Data Warehousing Concepts, Data Lake Architecture

Cloud & Data Engineering: Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure SQL Database, ETL/ELT Pipelines, Apache Airflow, SSIS, Azure DevOps

Tools & Platforms: Git, GitHub, Bitbucket, Power Automate, Looker, QlikView, Jupyter Notebook

Programming: Python (Pandas, NumPy, Matplotlib, Seaborn), Data Processing & Automation Scripts

Methodologies: Agile, Scrum, SDLC, Data Lifecycle Management