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About

🔍 I’m a Data Analyst with 3+ years of experience turning complex datasets into clear, actionable insights that drive business outcomes. Skilled in SQL, Python, Tableau, Power BI, and advanced Excel, I specialize in uncovering trends, building dashboards, and delivering predictive models that support decision-making at scale.

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My background spans healthcare and financial services, where I’ve helped reduce costs, prevent fraud, and improve efficiency by leveraging data to tell a compelling story. I thrive at the intersection of analytics and business strategy — translating numbers into insights that executives and teams can act on.

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I’m passionate about using data to solve real-world problems, whether it’s optimizing patient care, reducing operational inefficiencies, or strengthening risk management. Open to opportunities in data analytics, business intelligence, and data-driven consulting.📊 
 

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Education

Master of Science in Computer Science 

University of Texas at arlington, Arlington, Texas

CGPA: 3.6/4.0

Bachelor of Technology in Computer Science and Engineering

SR Engineering College, Telangana, India

CGPA: 8.63/10

Technical Skills

  • Data Analysis & Programming: SQL | Python (Pandas, NumPy, Scikit-learn, SciPy) | R | Excel (VBA, Pivot Tables, Advanced Functions)

  • Statistical Analysis & Machine Learning: Regression Analysis | Forecasting | Classification | Clustering | A/B Testing | Predictive Modeling

  • Data Visualization: Tableau | Power BI | Excel Dashboards | Matplotlib | Seaborn | Statistical Charts

  • Database Technologies: SQL Server | PostgreSQL | MySQL | Snowflake | Query Optimization

  • Business Intelligence: KPI Development | Trend Analysis | Performance Metrics | Executive Reporting

  • Data Management: Data Cleaning | ETL Processes | Data Validation | Quality Assurance

Projects

Sales data Analysis  
Image Classification for Wildlife Species
Java-Based Fault-Tolerant Transaction Management Using 2PC Protocol
Naïve Bayes Classifier for text Classification
August 2019
Stair Climbing Robot   
July 2020
Library Management System 
April 2021
Pass Matrix Password Authentication System 
April 2022
Predict Diabetes using Machine Learning Models 

Implemented SQL ETL mappings and designed a star schema to streamline data extraction, transformation, and loading processes, reducing data processing time by 30% and conducted EDA to clean and validate data. Developed an interactive Tableau dashboard leading to a 40% increase in stakeholder engagement and improved decision-making through visualizations of sales metrics, customer segmentation, and regional trends.

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Developed a 98% accurate animal image classifier using Python, TensorFlow, and machine learning/deep learning algorithms, Addressed data preprocessing challenges, managing 5% corrupted images and reducing overfitting, to enhance model accuracy and generalization. Achieved a 10% boost in classification accuracy and optimized GPU usage for 3x faster training speed boost, ensuring the model's robustness and reliability, resulting in a 40% reduction in GPU load.

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Developed and tested a Java-based distributed transaction management system using the 2-Phase Commit (2PC) protocol, successfully demonstrating fault tolerance and recovery in scenarios involving coordinator and node failures. The project effectively handled transactions across multiple nodes with zero data loss, showcasing an average recovery time under 2 minutes and enhancing system reliability by 40% in simulated network failure environments.

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Implemented a Naïve Bayes Classifier from scratch for text classification, achieving 54.3% accuracy on the Ford Sentence Classification Dataset without using external libraries.Conducted experiments including Laplace smoothing optimization, deriving top predictive words for each class, and exploring the impact of NLP techniques like stop word removal, showcasing proficiency in NLP and algorithmic implementation.

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A staircase climbing robot is built and implemented which can climb the step of given height without interrupting step with maximum stability.

ARDUINO SOFTWARE is used to connect arduino and Genuino hardware to upload program and operate the robot.

It is a web application that allows users to manage library resources such as books , keep track of stock availability, and conduct searches. Users will be able to see the site without registering, but they will be able to request a check-in only if they are registered.

JAVA and Spring MVC are used to implement REST API requests. The frontend application connects with the backend server through AJAX requests, passing data in JSON format.

To make passwords secured from shoulder surfing attackers this system is build.

Using SHA-1(Secure Hash Algorithm) and cryptographic hash function it is implemented by using java language.

It is a model performs early prediction of diabetics by taking 8 parameters, training and testing dataset and combining results with random Forest , Logistic Regression, Support Vector Machine, Naive Bayes algorithms.

Using Flask web page the prediction is displayed of the chances of getting diabetic in near future.

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