Summary
Overview
Work History
Education
Skills
Academic Projects
Certification
Custom
Timeline
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NAVEEN KRISHNA MADDULA

New Jersey

Summary

Results-driven Data Analyst with a proven track record at Ford Motor Company, leveraging advanced skills in Python and Tableau to enhance data-driven decision-making. Achieved a 32% reduction in unexpected vehicle downtimes through innovative analytics and cross-functional collaboration, while implementing robust ETL processes to ensure data integrity and operational efficiency.

Overview

6
6
years of professional experience
1
1
Certification

Work History

Data Analyst

FORD MOTOR COMPANY
New Jersey
06.2023 - Current
  • Led end-to-end analysis of connected vehicle telemetry data using BigQuery and Python, processing over 50 TB of daily data to identify maintenance patterns, resulting in a 32% reduction in unexpected vehicle downtimes.
  • Developed interactive Tableau dashboards for real-time vehicle performance monitoring, serving over 300 stakeholders across five departments, with 99.9% uptime, reducing decision-making time by 45%.
  • Implemented an A/B testing framework using Python and SQL for feature adoption analysis, increasing user engagement by 28% and feature utilization by 40% across the connected vehicle platform.
  • Created an automated data quality monitoring system using Great Expectations and Python, reducing data inconsistencies by 70%, and saving 15 hours per week in manual validation.
  • Designed and maintained a KPI tracking system in Power BI for vehicle diagnostic accuracy, improving maintenance prediction accuracy from 75% to 92% through iterative refinement.
  • Built predictive models using Python (Scikit-learn) to forecast vehicle component failures, resulting in a 25% reduction in warranty costs and a 35% improvement in maintenance scheduling.
  • Orchestrated the migration of legacy reports to a modern BI stack (Looker + BigQuery), reducing report generation time by 60% and achieving $200K in annual cost savings.
  • Utilized advanced analytics tools such as SAS, SPSS, Excel PowerPivot, to manipulate large volumes of structured and unstructured data sets.
  • Designed and implemented interactive visualizations using Tableau, Power BI, and other tools.

Data Analyst

TECH MAHINDRA LIMITED
India
12.2019 - 12.2021
  • Engineered ETL pipelines using Python and SQL to process 500GB+ daily telecom network data, improving data freshness by 4 hours and accuracy by 45%
  • Developed comprehensive Tableau dashboards for network performance monitoring, serving 200+ users with 15-minute refresh cycles, increasing operational efficiency by 30%
  • Implemented automated anomaly detection system using Python and statistical models, reducing network outage detection time from 30 minutes to 5 minutes
  • Created Python-based reporting automation suite, eliminating 20+ hours of weekly manual effort and reducing human error rate by 95%
  • Designed customer churn prediction model using SQL and Python, identifying high-risk customers with 85% accuracy, enabling retention team to reduce churn by 18%
  • Built real-time customer experience monitoring system using Power BI and SQL, improving customer satisfaction scores by 25% through proactive issue resolution
  • Implemented data governance framework using Collibra, improving data documentation compliance from 40% to 95% across 50+ datasets

SQL Developer

NITIDO IT SOLUTIONS PVT LTD
India
01.2019 - 11.2019
  • Designed and optimized complex SQL queries and stored procedures, reducing query execution time by 40% for critical business reports
  • Implemented database schema modifications and improvements, resulting in 30% better database performance
  • Developed and maintained ETL processes for data warehouse loading, ensuring 99.9% data accuracy
  • Collaborated with business analysts to optimize reporting queries, improving report generation time by 50%
  • Developed resource utilization dashboard monitoring 40+ database instance in real-time
  • Built live query performance dashboard tracking 100+ critical queries with 15-second refresh rate
  • Get familiar with database systems like MySQL, PostgreSQL, or SQL Server
  • Understand how data is stored, organized, and retrieved
  • Write SQL queries to fetch, update, or delete data
  • Learn how to make queries faster and more efficient
  • Help to create, and design database tables, relationships, and structures based on project needs

Education

Master’s - information systems

University of Memphis

Bachelor’s - electronic and communication Engineering

K L University

Skills

  • Tableau
  • Power BI
  • Excel (Advanced)
  • Looker
  • Interactive dashboards
  • Data modeling
  • A/B Testing
  • Statistical Analysis
  • Predictive Modeling
  • SQL
  • Python (Pandas, NumPy, Scikit-learn)
  • R
  • SAS
  • SPSS
  • PostgreSQL
  • MySQL
  • Snowflake
  • Google Cloud
  • Azure
  • AWS
  • Google Big query
  • Data Storytelling
  • Cross-functional Collaboration
  • Project Management
  • Agile
  • JIRA
  • SCRUM
  • GitHub
  • Docker
  • CI/CD pipelines (using Jenkins build tool)
  • Analytical thinking
  • ETL processes
  • Data warehousing
  • R programming

Academic Projects

Tableau | Developed vehicle insurance cross-sell model for health insurance customers

· Identified geospatial hotspots for vehicle insurance based on accident & demographic data

· Developed predictive models to identify potential customers based on health insurance claims and adjacent data

· Developed customer segment-wise bundled products and pricing models based on underwriting risk

· Improved team efficiency by 35% by automating ETL and dashboard updates

· Built interactive Tableau dashboards and hosted on PHP platform over a data & analytics stack of SQL & R.

Certification

Issued on: Mar 11, 2025 by IBM - Coursera

Custom

Project: DIGITAL PENETRATION DATA

· In this project we had exhibited an effective approach for the analytics of demographic data and here we study and learn various process of approaching and do analysis using different languages like python and R-Programming.

· We have used Python for analyzing Demographic Data that was collected during a Survey between different countries.

· Other data like Digital penetration data Survey consists of data of people in nearby villages containing their living status and their opinions on different digitalization techniques for digital banking and some demographic data.

· We have followed the One hot encoding algorithm for the conversion of data into the binary format and, we have analyzed the basketball data all these 3-survey data are analyzed using python in Jupiter notebook.

· We have visualized the relations between the certain selected columns by using different plotting techniques and libraries in the demographic way.

Timeline

Data Analyst

FORD MOTOR COMPANY
06.2023 - Current

Data Analyst

TECH MAHINDRA LIMITED
12.2019 - 12.2021

SQL Developer

NITIDO IT SOLUTIONS PVT LTD
01.2019 - 11.2019

Master’s - information systems

University of Memphis

Bachelor’s - electronic and communication Engineering

K L University

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