Pranay Kumar Verma


Fairfax County

Software Develeopment Engineer at Amazon, Advertising Technology.
Computer Science Graduate from Syracuse Univeristy.
7+ years of professional work experience in mobile and web development.
Skilled in Full stack development and tools.

Experience

Software Development Engineer

Amazon, Advertising Technology
June 2021 - Present

Graduate Teaching Assistant - Software Implementaion

Syracuse Univeristy
  • Worked with Professor to design and deliver the Software Implementation course which covers nuances of Agile/Scrum methodology and its significance in SDLC.
  • Assisted faculty to create project strategies and Grade projects and homeworks.
  • Collaborated to create class activities and build reporting templates for the benefit of students while enforcing the framework in their course project.
January 2021 - May 2021

Graduate Teaching Assistant - Analysis Of Algorithms

Syracuse Univeristy
  • Conducted recitation lectures and mentored the students with coursework, homework and exams.
  • Assisted faculty to create exam strategies, exams and homework and structure the grading process.
August 2020 - December 2020

Senior Software Developer

Mobile Application Programmer & Application Package Management Lead
DXC Technology (Formerly Known as CSC)
  • Conceptualized and developed offline framework for Hybrid Mobile Application developed using AngularJS & Cordova.
  • Improved data fetch performance by 30% by optimizing SQL procedures, restful webservices and the front-end code.
  • Integrated SITHs card authentication for use by the swedish market.
  • Served as Onsite Coordinator, solved high priority customer problems, part of gate meetings and Hotline support.
  • Accountable for product quality before delivery, ensure deliverables are on time, QC Reports, defect trend analysis.
  • Led Build and Deployment team: proactively involved in creating Build Plans & Merge Strategies with 3 team members.
February 2018 - July 2019

Software Developer

Web and Mobile Application Programmer
DXC Technology (Formerly Known as CSC)
  • Created multiple configurable directives and components to improve reusability, potentially reducing 6,000+ lines of code.
  • Worked on development and maintainence of website built using .Net framework and MVC architecture.
  • Developed various new modules for Hybrid Mobile Application made using AngularJS & Cordova.
  • Automated part of the build process using PowerShell scripting & Jenkins, saving 3 hours per build in addition to manual work.
September 2015 - January 2018

Education

Syracuse University

Masters of Science
Computer Science - Machine Learning and Neural Networks Track

GPA: 4.0, Summa Cum Laude

August 2019 - May 2021

Amity Univeristy

Bachelors of Technology
Computer Science - Web and Mobile App Develeopment Track

GPA: 3.33

July 2011 - May 2015

Skills

Programming Languages & Tools
Frameworks
  • Hybrid Mobile Applications
  • Mobile-First, Responsive Design
  • SQL and SQL lite Databases
  • Cross Browser Testing & Debugging
  • Cross Functional Teams
  • Agile Development & Scrum
  • MVC Architectutre
  • Machine Learning and Deep Learning Algorithms and tools

About Me

“Nothing in this world can take the place of persistence. Talent will not: nothing is more common than unsuccessful men with talent. Genius will not; unrewarded genius is almost a proverb. Education will not: the world is full of educated derelicts. Persistence and determination alone are omnipotent..” ― Calvin Coolidge

I try to live by these words and remind myself to persist when the going gets tough. I try to seek a challenge whenever possible, as it helps me face my fears and prepare me for a better tomorrow. My path of learning has always been the one that forces me to work harder. Like being handed work in a technology which I had never heard of when I was employed at DXC and then slowly learning and mastering it. I finally became so good at it and gained a deep understanding of the architecture that I was promoted to be the technical lead for my team.

In my second year working in DXC, I was given the opportunity to work for the mobile app development team for VITAE Go. I jumped on that opportunity and this was one of my most rewarding decision of my life. I had the opportunity to get my hands dirty with tons of new technologies and softwares. It helped me broaden my level of understanding and knowledge. I got direct exposure to strategic decision making and an opportunity to work with many counterparts in Denmark and Sweden which in turn helped me understand problems from different socio-cultural perspectives.

After almost 4 years of working for DXC, I wanted to learn more and decided to pursue my Master of Science in Computer Science from Syracuse University.

When I am not sitting with my laptop, I usually like to play snooker or basketball.

I love making new professional connections. Reach out to me if you want to talk about technology or sports.

Projects

ProcSmart
  • ProcSmart is a smart online proctoring system for real time activity monitoring of candidates during an online examination.
  • The application intends to solve the problems faced by existing proctoring systems and include some extra features, which will enable better efficiency.
  • An autonomous proctoring system which does not entail any live proctoring or recordings, rather the system will monitor the session and based on ML and AI models and Flag users when an anomaly is detected in the session.
September 2020 - December 2020

Waste Classification using CNN's
  • Classified waste into recyclable and organic using DenseNet and Simple CNN architectures achieving accuracy of 95%.
  • Recyclable trash was classified into its subcategories (cardboard, glass, metal, paper, plastic) using a VGG 16 inspired CNN architecture.
  • A two stage model was built which allowed trash to be classified into recyclable and organic, with recyclable trash further being classified into its subcategories using the above described models.
October 2020 - November 2020

Google Web Traffic Time Series Analysis
  • This project is focused on predicting the future values of the Google web traffic. It is considered as challenging to forecast the future value of the time series data for web traffic because of the unpredictability of the factors contributing to the website’s traffic.
  • The data that I have chosen to work on is the Wikipedia web traffic data. This data analysis is focused on the factors contributing to the wikipedia web traffic like the day, duration, holidays, weekends and any other major events like elections and Olympics. And later in the project I have explored on the multiple algorithms which can work well with forecast of the time series data.
May 2020

YouTube Sentiment Analysis and Predicting Trends
  • The project focused on using different Sentiment Analysis Techniques such as Vader, Afinn and NRC Lexicon on comments of top 200 videos of a YouTube channel specified by user. All Data was scraped in real time using the YouTube Data API v3.
  • Baseline analysis was performed by manual classification of 1200 comments and Vader outperformed other Sentiment Analysis Techniques.
  • Data was now grouped by date, creating a Time-Series dataset, to give us insight in to daily comment trends. This was then used to predict future sentiment trends using Machine Learning and Neural Networks Algorithms such as Linear Regression, Polynomial Regression and Long Short Term Memory.
  • Achieved accuracy of 96% predicting upcoming comment sentiment using the earlier analysis.
February 2020 - April 2020

Predicting Financial Markets
  • This project was an experiment to predict stock prices and identify the best machine Learning algorithm among the 4 methods used in the project.
  • Used Support Vector Regression, Linear and Polynomial Regression, Moving Average and Long Short Term Memory to learn trends & predict future stock prices.
  • Developed in a way that the stock could be selected by the user at runtime.
  • Evaluated the methods and the best yielded confidence of 95%.
October 2019 - December 2019

Flight Delay Prediction
  • Implemented Linear Regression, Ridge Regression, Random Forest and Boosted Linear Regression on an airline delay dataset to predict the delay time of the given input.
  • Implemented K neighbors classifier, Logistic regression and decision trees on an airline delay dataset to predict if the flight is delayed.
  • Based on the Mean Squared Error and R2 score, Linear regression and Boosted linear regression produced the best result and Random Forest Regression without intercept had the highest MSE, hence, the least preferred method for predicting delays.
  • The two best method for classification were Logistic regression and K neighbors classifier, both of them yielding the highest F1, Precision and Recall.
October 2019 - November 2019

Movie Recommender System
  • Created a Model Based and Item Based Collaborative Filtering Recommendation System to predict user ratings on different movies of movie lens dataset.
  • Created both item-wise and user-wise classifiers then based on their similarity perform predictions.
November 2019

Order Management and Report Creation
  • Created a full stack Angular 7, TypeScript application using WCF Restful Webservices and SQL.
  • Provided authentication and authorization functionalities using PassportjS.
  • Extensive use of HTML5, CSS3 and Bootstrap to create visually appealing and responsive website.
  • Integrated RESTful routing for the functioning of the website.
June 2019

Vehicle Diagnostic and Performance Application
  • Developed an Android Application which enables the user to connect to their car and check its performance or any fault codes generated on their handheld device.
  • The application enables the user device to connect to the vehicle’s Engine Control Unit (ECU) using an OBD-II connector.
  • It provides the ability to see what a particular vehicle is doing in real-time, lookup fault codes generated, timing advance, sensor data and more.
January 2015 - May 2015

Certifications & Awards

  • Awarded Outstanding Student in Computer Science by chair of department for maintaining perfect 4.0 GPA and being Top 5% in every class
  • AWS Fundamentals Specialization – Amazon Web Services offered by Coursera   [View Certificate]
  • Modern React with Redux   [View Certificate]
  • Getting Started with AWS Machine Learning – Amazon Web Services offered by Coursera   [View Certificate]
  • Neural Networks and Deep Learning – DeepLearning.ai offered by Coursera   [View Certificate]
  • Machine Learning – Stanford University Online offered by Coursera   [View Certificate]
  • Machine Learning with Python - Level 1   [View Certificate]
  • Python for Data Science   [View Certificate]
  • Artificial Intelligence and Machine Learning Basic   [View Certificate]
  • DXC Technology - Awarded performer of the year for continued innovations and stand out performance in the team.