Software Engineer Data Analytics

USA • **********@*****.*** • +1-774-***-****

BHARGAV ADSUPALLI

Software Engineer

PROFESSIONAL SUMMARY

Detail-oriented software engineer with hands-on experience developing responsive web applications using Angular, TypeScript, HTML, and CSS. Skilled in data analysis and visualization, with a strong ability to translate user needs into efficient, scalable front-end solutions. Experienced in integrating APIs, optimizing performance, and improving UI/UX through structured design and modern development practices. Seeking to apply technical skills and a growth mindset in a collaborative, fast-paced development environment.

EMPLOYMENT HISTORY

SOFTWARE ENGINEER Aug 2022 - Aug 2023

Manhattan Associates Bengaluru, India

SOFTWARE INTERN Aug 2022 - Jun 2023

Manhattan Assosiates Bengaluru, India

EDUCATION

MASTER OF SCIENCE (MS): DATA ANALYTICS

Clark University Worcester, Massachusetts

INTEGRATED MTECH SOFTWARE ENGINEERING

Vellore Institute of Technology Tamil Nadu, India

Contributed to the development and maintenance of 5+ Angular applications using TypeScript, HTML, CSS, and JavaScript, focusing on responsive design and component reusability. Implemented secure login functionality using JSON Web Tokens (JWT), improving application data protection. Collaborated with backend developers to integrate 10+ RESTful API endpoints, enabling data rendering. Built and styled 15+ UI components using Angular Material (charts, forms, tables), enhancing usability and user engagement.

Designed visual assets and layouts that supported consistent cross-platform user experiences. Performed code reviews and validation to ensure compliance with web standards, achieving cross-browser compatibility across 8+ major browsers and devices.

Developed a small-scale internal tool using AngularJS and Node.js to automate routine tasks, reducing manual effort by approximately 30%.

Created reusable components and custom directives to streamline development in future projects. Conducted testing and debugging on various devices and screen sizes to ensure a smooth user experience. Implemented an Angular-based application that improved UX and increased client engagement by simplifying navigation and modernizing UI design.

Developed 10+ reusable components, streamlining development cycles and promoting UI consistency across projects. Performed in-depth performance analysis, identifying front-end bottlenecks and optimizing load times, resulting in a ~30% improvement in responsiveness.

Maintained project documentation and onboarding guides, reducing ramp-up time for new developers by approximately 40%.

Collaborated with cross-functional teams to align feature delivery, ensuring timely updates and high code quality. Improved application architecture to support scalability and modular development, enabling faster deployment of new features.

Leveraged user feedback and analytics to enhance feature sets, leading to noticeable improvements in user satisfaction metrics. Integrated third-party APIs to expand application functionality and improve user convenience. CERTIFICATIONS

AI ASSOCIATE CERTIFICATION Feb 2025

Salesforce

ANGULARJS CERTIFICATION Mar 2023

Udemy

ADVANCE JAVASCRIPT CERTIFICATION Mar 2023

Udemy

NODE JS CERTIFICATION Oct 2021

ShapeAI

FULL STACK WEB DEVELOPMENT CERTIFICATION Oct 2021

ShapeAI

SKILLS

JavaScript, AngularJS, Node.js, SQL, Java, ReactJS, HTML, CSS, TypeScript, Python, Data Analysis, Data Visualization, Predictive Modeling, RESTful Services,

ADDITIONAL INFORMATION

ONLINE NEWS POPULARITY ANALYSIS

LINKS

Portfolio: bhargav-cv.vercel.app, Bookmyshow Clone: bookmyshow-clone-432e5.web.app, Qiuz Application: quick-quiz.vercel.app, Git Repository: github.com. Conducted an in-depth analysis of online news articles to determine key factors influencing audience engagement, social sharing, and overall popularity.

Performed a comprehensive statistical and machine learning analysis on a dataset of online news articles to predict popularity metrics.

Utilized Python libraries including NumPy, pandas, scikit-learn, and matplotlib for data preprocessing, EDA, and model development.

Applied correlation analysis, feature selection (e.g., mutual information, chi-square), and dimensionality reduction (PCA). Developed and evaluated multiple supervised learning models (logistic regression, random forest, SVM) using cross-validation and performance metrics such as ROC-AUC, F1-score, and precision-recall curves. Optimized hyperparameters via grid search and implemented model interpretability techniques to identify key drivers of article popularity.

Utilized data preprocessing techniques to clean and structure the dataset, ensuring accurate analysis and meaningful insights. Applied statistical methods and machine learning models to identify patterns in article attributes. Developed predictive models to forecast article engagement. Created interactive visualizations using Matplotlib, Seaborn, and Tableau. Employed Python, SQL, and Excel for data analysis

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