Sourav Singh

802 - 311 Bell St S · Ottawa, K1S 4K1 · (437) 679-2993 · sourav.s.rathore@gmail.com

Technically advanced Java Developer with 7 years of work experience facilitating cutting-edge engineering solutions. Offering expertise in Java, Spring MVC, and RESTful API development. Strong understanding of microservice architecture, continuous integration, and deployment practices. Extensive expertise in EdTech, IoT Platforms, E-commerce, Retail, Supply chain management, and POS application domains. Having exposure to Software Development Life Cycle (SDLC), Experience working with Agile, SAFe, and Waterfall Models.

Experience

Software Developer Consultant

Modern Campus

• Involved in the development and maintenance of the Destiny One web platform, which supports the business operations of over 1800+ schools across the globe
• Translated business requirements into functional specifications and identified optimal technologies, reducing development time by 15% and resulting in savings of over $50,000 in development costs
• Successfully integrated Moneris payment gateway API with Destiny One web platform, which resulted in a 25% reduction in transaction failures and improved business performance for the schools
• Conducted root cause analysis and resolved bugs and issues, reducing downtime by 15% and improving platform reliability and stability
• Provided customized business logic and designed and updated over 50 custom crystal reports for schools, resulting in significant time savings for school administrators and helping businesses to engage more numbers of students
• Developed the UI layer using Spring beans, JSP, JavaScript, jQuery, JSTL, XML and CSS, improving the user experience and increasing platform usability

October 2022 - Present

Senior Software Developer

SD Global Services

• Played a key role in the development of the Destiny One web platform, which supported the business operations of multiple schools and served thousands of students
• Led and supervised the India development team in the successful completion of the Student Profile and Payment gateway integration module, resulting in the platform's ability to process payments securely and efficiently.
• Worked collaboratively with stakeholders following the Agile Scrum software development process, ensuring that project requirements were met on time and within budget
• Customized the D1 web platform based on business client requirements, resulting in improved platform functionality and enhanced user experience
• Developed and updated Spring Restful APIs for D1 web

November 2021 - August 2022

Senior Engineer

Carrier Global

• Developed and implemented APIs to generate and validate commercial licenses for the Carrier MyWay IoT solution, which were critical for the commercialization of the product, enabling the sales team to easily and efficiently generate new licenses for customers
• Designed and developed drivers from scratch for BACnet light, HVAC and Thyssenkrupp Elevator systems, which enabled the MyWay IoT platform to support a wider range of devices and increased the platform's capabilities
• Independently researched and analyzed BACnet, Health Level Seven (HL7) to develop new drivers to support the MyWay IoT platform, which resulted in the successful release of our product
• Supervised service providers team to successfully develop and integrate HL7, and Integrated Lighting Controls (ILC) with the MyWap App
• Played a key role in project estimation, development, and design of documents, which resulted in the timely completion of over 10+ sprints
• Mentored and held knowledge transfer sessions to educate other developers on TCP and BACnet protocols, resulting in a 25% increase in team productivity
• Facilitated and oversaw the product deployment process, ensuring that all steps were completed accurately and efficiently. This involved working closely with cross-functional teams, including developers, quality assurance engineers, and project managers, to coordinate the release of new features and updates to the software
• Managed the communication and coordination between internal teams and external stakeholders to ensure that the deployment process was seamless and timely

April 2020 - October 2021

Software Engineer

Yash Technologies

• Performed extensive bug fixing for the Stellar Support eCommerce website, identifying and resolving over 100 bugs to improve the user experience and increase customer satisfaction
• Implemented numerous enhancements to improve the overall website performance, resulting in a 15% increase in website speed boosting customer engagement
• Played a key role in the migration of the authentication service from oAuth to Okta, which improved the security and reliability of the website's authentication system
• Wrote Junit and Mockito test cases to improve the code coverage to ~95%, which resulted in a 20% reduction in the number of bugs and improved the overall quality of the codebase
• Facilitated production support for the deployment of the application, ensuring that the website was running smoothly and providing timely assistance to customers, resulting in a 90% decrease in customer complaints

April 2019 - April 2020

Senior System Engineer

Infosys

• Wrote well-designed, testable, efficient code to support dynamic and complex IT solutions, resulting in a reduction in software bugs and increasing overall system performance
• Developed REST APIs for client-side implementation of the product for the HSBC Iceberg project
• Utilized Anypoint MuleSoft ESB to design APIs and improve test coverage, resulting in a 30% reduction in the time required to create new APIs
• Developed and executed Junit and Mockito test cases to ensure the quality and accuracy of the code, resulting in a 90% reduction in the number of software bugs and increasing system stability
• Mentored junior developers on best practices for writing efficient and effective code and provided guidance on the use of Anypoint MuleSoft ESB and other development tools

November 2018 - April 2019

Associate Consultant

Capgemini

• Successfully led and supervised a team of 7 individuals in the development and delivery of automated test suites for McDonald's POS and Kiosk v6 application, in markets including Saudi Arabia, Spain, and Japan. This resulted in a 70% reduction in the time required for manual testing and a 30% increase in testing accuracy
• Collated data for billing requirements and demonstrated project overview to the leadership and CXOs team, resulting in successful project delivery within the given timeline and budget constraints
• Contributed to the development and enhancement of SCM tool (RMS) for Statefarm Insurance
• Implemented logging facility and adapted a modular approach for a better debugging perspective for the existing RMS tool, resulting in a 40% reduction in the time required to identify and resolve software bugs
• Collaborated with the team to develop and execute test cases to ensure the quality and accuracy of the code, resulting in a 90% reduction in the number of software bugs and increasing in system stability

December 2015 - November 2018

Education

Carleton University

Masters in Applied Business Analytics

Technolgy Innovation Management

September 2021 - April 2023

West Bengal University of Technolgy

Bachelor of Technology

Computer Science and Engineering

CGPA: 7.90

July 2011 - June 2015

Skills

Programming Languages & Tools

Workflow

Requirement gathering and analysis
Technologies RnD
Backend Development
Software Testing & Debugging
Agile Development & Scrum

Academic Projects

Reviewing techniques to improve BERT Question Answering Model

Abstract

BERT’s existing question answering models are very expensive to train and maintain, so their practical use in the real world is difficult. The purpose of this paper is to analyse some of the existing methods for improving the BERT QA model. This study will provide a brief background on the application and suggest an improved approach to implementing the BERT model for a QA system. This project aims to analyze if BERT base QA model performance can be further improved using the combination of text pre-processing, adding an extra linear layer to the model and using the Adam optimizer. The generated question-answering BERT model is evaluated against SQuAD 1.1 dev benchmark data set. In particular, this project demonstrates how to create a custom model and ways to improve the performance of a model, this review also explores the challenges and issues with BERT for the QA system.

Read more.
Exploring ways for a better interpretation of topic models

Abstract

Topic modelling is a technique used to automatically identify the underlying topics in a large collection of unstructured text data, such as news articles, social media posts, or customer reviews. This method has gained importance due to the increasing volume of unstructured data available on the internet. Topic modelling helps to identify the main themes or topics present in the text data without the need for manual reading and categorization. This can help to gain insights into the key issues or concerns that people are discussing, identify patterns in the data, and make data-driven decisions based on the insights obtained from the text data. The applications of topic modelling are wide-ranging, including social media analysis, market research, content recommendation, and customer feedback analysis. Overall, topic modelling is a valuable tool for gaining insights from large volumes of text data and can lead to more informed decision-making in various industries, but at the same time, it can be a complex process that requires domain knowledge, research, and additional text analytic tools. To extract meaningful insights from topic modelling, it is important to not only identify the main themes or topics in the text data but also to understand the nuances and relationships between them. This project will explore processes that combines the results of the LDA topic model with text summarization algorithms to achieve a better interpretation of the topic model results. The process of combining topic modelling with text summarization can be challenging, as it requires the selection of appropriate summarization techniques and careful consideration of the impact of summarization on the underlying topics. Hence this project will also experiment with different approaches for selecting the associated documents within the topic, in order to identify the best possible ways of choosing the document for a better topic model interpretation.

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Bike Theft Analysis in Ottawa

Abstract

The developed tool is a web-based application that utilizes machine learning models and AI to demonstrate current trends in bike theft in Ottawa while also predicting future bike thefts based on available data. By analyzing available data, the tool provides valuable insights into the latest trends and patterns in bike theft in the area, aiding in the development of proactive measures to combat the problem. The application employs machine learning algorithms to analyze historical data on bike theft in Ottawa and predict future thefts based on the patterns observed. The AI-powered tool utilizes data from various sources, including the Ottawa Police Service database, to generate predictive models capable of forecasting bike theft incidents accurately. The tool is highly beneficial to the Ottawa community, especially bike owners, as it allows them to take proactive measures to prevent bike thefts. Additionally, the data generated by the tool can also aid law enforcement agencies in developing effective strategies to curb bike thefts in the area. Overall, the web-based tool is a highly advanced solution that combines machine learning and AI technologies to address the growing problem of bike thefts in Ottawa. Its ability to predict future thefts accurately makes it a valuable resource for community members and law enforcement agencies, ultimately promoting bike safety in the area.
Youtube Comments Sentiment Analysis

Abstract

Evolution in technology has led to emergence of various social media platforms like Facebook, Youtube and Twitter which has now become a necessity in day to day life. People upload videos, pictures, share news and information on such platforms. Youtube is the widely used platform for uploading and sharing videos and the most used website. Our goal is to identify, extract, and study the feelings and emotions of comments posted by customers and viewers of the video to understand the degree of positive or negative. This would give an overall analysis of the customer satisfaction pertaining to a certain product. This will also give an idea to content creators about the public acceptance of their videos and help improve quality. In this study, we have collected user comments on three videos on iPhone 13 unboxing and then using our machine learning model, we analysed the sentiments of comments and then categorized them into positive and negative.
Read more.

Interests

Studying Masters in Applied Business Analytics at Carleton University 2021-23. Apart from being a software developer, I enjoy most of my time playing online games and reading about latest technologies updates. I love cooking and experimenting with recepis during my spare time.

I also enjoy reading and following a number of sci-fi genre movies and television shows, I am an aspiring data scientist, and I am super excited to see AI being more intelligent than human one day.

Certifications

JEE L1 Certified by Igate University and Globsyn Skills
ASP.net Certification from Ardent Infotech
MS Dynamics NAV by Dynamics Global Infotech
Machine Learning using Python from Udemy

CONTACT

Sourav Singh

Work Phone: +1 (437) 679-2993

Email: sourav.s.rathore@gmail.com

Awards