Rahul Victor Sunkara

Enthusiastic, dedicated, and detail-oriented Software Engineer with over 3 years of experience in developing, deploying, and testing fully functional websites and applications. Pursuing a Master’s degree With a 4.0 GPA from University of Arizona with a focus on advanced concepts in Machine Learning and AI. Strong problem-solving abilities and a solid understanding of scripting, coding principles, and software design. Skilled in Machine Learning, Data Analysis, and Predictive Analytics, with hands on expertise in Python, SQL, Tableau, Power BI, TensorFlow, Pandas, and Scikit-learn. Specializes in data mining, visualization, and developing machine learning models.

Centrica Field Ops Project, 12/2021, Present :

• Working as a Full Stack Programmer on the FieldOps project, I contribute to the development of RESTful APIs and microservices while assisting the team in creating and testing user stories. By conducting root cause analysis and resolving issues, I help the Onshore team make informed decisions on Engineer Supply and Demand. Additionally, I provide support to DevOps in deploying and maintaining fault-tolerant systems and pipelines, ensuring continuous project success.

German Bank Loan Default Prediction, Aug 2024 - Sep 2024:

• Developed and fine-tuned machine learning models to predict loan defaults using a German bank dataset, analyzing features like checking balance, employment duration, and loan amount. Conducted EDA with visualizations to identify key relationships, and preprocessed data by handling missing values, encoding categories, and standardizing features. Implemented models such as Logistic Regression, Decision Trees, Random Forest, SVC, XGBoost, and Gradient Boosting, optimizing hyperparameters with GridSearchCV. Evaluated performance using accuracy, precision, recall, and F1-score for balanced predictions.

The Movie Data Base movie data scraper, Feb 2024 - Feb 2024 :

• A Python-based web scraper designed to collect and organize movie-related information from The Movie Database (TMDB). Using libraries like requests, BeautifulSoup, and pandas, the project extracts data such as movie titles, ratings, genres, and cast details from multiple pages. The scraped data is structured into DataFrames and saved as a CSV file, making it suitable for further analysis or integration into other projects.

Data extraction and analysis from social media platform YouTube, Jan 2024 - Feb 2024:

• The Project entails utilizing the YouTube API through Python for data extraction related to the "avatar movie." It involves setting up the API key, extracting video details, and obtaining statistics for the top 50 videos in the US. Analysis includes sorting videos by top comments, retrieving comments, exporting data in JSON format, and calculating the likes vs views ratio for top videos with the most comments.

Twitter Clone App, Sep 2022 - Oct 2022:

• The Twitter Clone App is a social media application that allows users to create profiles, post tweets, follow other users, and interact with their content. It includes features such as trending topics, a search function, and customization of user profiles, but no direct messaging functionality. Built Using CORS, Angular11 for the FrontEnd and .NET Core, WebApi, and SqlServer for Database, and deployed into an Azure container using docker.

Retail Management System, Oct 2021 - Dec 2022:

• Developed and Led a team in creating the Retail Product Management Application that provides additional support to the organization by giving them a platform to showcase their products to a larger audience Using Microservices, .NET Core, Web API, NUnit, Restful API, JWT Token-based authorization, and SQL for creating the Middleware and Backend, and Angular for Front End. Dockized the microservices and pushed them to Docker Hub. Hosted the application in a production environment on Azure using DevOps and Code Commit.

Online Car Rental System, Aug 2021 - Sep 2021:

• Developed an Online Car Rental application for the internship to create strong middleware by creating Microservices that handle E2E HTTP Requests from users. Used
  .NET MVC, SQL Server, JWT Token-based authorization, HTML, and JavaScript for creating the microservices. Dockized the microservices and pushed them to Docker Hub. Provided different functionalities to the application following the best practices of application development like Modularity, Security, Scalability, Unit testing, and Design principles.

• Promoted to Junior Software Engineer within 2 months, earning the Coral Award for exceptional client service.
• Achieved Cognizant Accreditation.
• Received client acknowledgment for exceptional work and assistance.