Software Developer Development Engineer

Vaibhav Sankaran

+1-857-***-**** # *****************@*****.*** ï linkedin.com/in/vaibhav-s-2408 § github.com/svaibhav07codez Experience

Verizon Data Services India Pvt. Ltd. Chennai, TN, India Software Development Engineer - II Dec 2023 – Jul 2024

• Led the backend development for the eSIM Transformation project in the Verizon web application and My Verizon mobile app, enhancing Verizon’s digital sales by developing and delivering complex user stories.

• Recognized for delivering 22 Jira story points worth of user stories in one sprint, where 8 is usually the max for one developer.

• Collaborated closely in an Agile model with cross-functional teams from the planning and grooming stages through to going live.

Verizon Data Services India Pvt. Ltd.

Software Development Engineer - I Jul 2022 – Nov 2023

• Back-end software developer for ’+Play’, a highly lucrative product for Verizon’s business.

• Recognized for driving innovation in Verizon India’s 15-member innovative team, InnoHub, by crafting intuitive solutions that empower customers with a clear purchase progress tracker, thus indirectly improving the NPS score. Verizon Data Services India Pvt. Ltd.

Software Developer Intern Feb 2022 – Jun 2022

• Developed and maintained the ’AddOns’ project for Verizon Web, delivering innovative solutions focused on security to address user challenges/problems, while enhancing user experience (UX) and user interface (UI) functionality.

• Analyzed and meticulously documented complex customer flows and their implementations, gaining deep insights into user behavior, and facilitating future maintenance and updates. Education

Khoury College of Computer Sciences, Northeastern University Boston, MA, USA Master of Science in Computer Science Sep 2024 – Present

• GPA: 3.83/4

• Member of Artificial Intelligence Club and Graduate Student Government Sri Sivasubramaniya Nadar College of Engineering (SSN), Anna University Chennai, TN, India Bachelor of Eng. in Computer Science and Engineering Sep 2018 – Jun 2022

• CGPA: 8.42/10

• Received the Meritorious Sports Scholarship twice (2018-19 and 2020-21) for excelling in both academia and sports. Technical Skills

Languages: Java, Python, Php, React JS, Node JS, HTML/CSS, SQL, C, C++, C#, Matlab, Linux Frameworks: Git, JUnit, Rest APIs, Spring Boot

Databases: SQL, MySQL, MongoDB

Methodologies: Agile, Kanban, Scrum, CI/CD pipelines Cloud & DevOps: Kubernetes, AWS, Jenkins, Microsoft Azure Tools & Other: Eclipse, STS, Android Studio, VS Code, Algorithms, Data Structures, Object Oriented Programming Projects

Guardians Gambit - Reinforcement Learning based multi-agent game AI, Python, Tiled Sep - Dec 2024

• Designed a bank heist simulation leveraging artificial intelligence through Q-learning to implement reinforcement learning strategies. Used Tiled platform for game environment development.

• Rewards and Penalties for the agents are based on: Game duration, Thief grabbing the cash bag, reaching the terminal area, camera range, Guard - Thief proximity

Image Manipulation and Enhancement (access on request) Java, Swing Sep - Dec 2024

• Using design patterns, created an MVC model where an image can be loaded, and various operations like save, blur, sharpen, sepia, etc. can be performed.

• 3 modes like GUI, text-based, and script file mode are supported while running the jar file. Also, multiple image formats are allowed.

Hyperparameter tuning in traffic forecasting Python, Data Analytics, Machine Learning Jan - Jun 2022

• Proposed a system based on Meta’s additive regressive time series forecasting model - Prophet, which accommodates selected exogenous factors, to best capture the stochastic nature of traffic.

• Improved the model by using Bayesian-directed search techniques for optimizing the most crucial model hyperparameters to increase forecasting accuracy.

Publications

Lakshmi Priya S R, Suresh J, Sharan G, Snehapriya M, Vaibhav S: ”Effects of Exogenous Factors and Bayesian-Bandit Hyperparameter Optimization in Traffic Forecast Analysis” {URL: Springer link } Used Meta’s Prophet model integrated with Bayesian-directed search techniques to optimize crucial hyperparameters.

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