Jaideep Sai Resume

1. Jaideep Sai K Email : jaideepsai@yahoo.com
 www.jaideepsai.com  jaideepsai Mobile : (813)-734-0519
Summary
Creative full-stack developer with strong programming background and over 4 years’ experience in fast-paced
agile environment, extensive experience in building user-centric web applications, scalable API’s.Proficient in
business intelligence ,data engineering/warehousing ,machine learning and data science concepts.
Education
• University of South Florida Tampa, FL
Master of Science in Business Analytics and Information Systems Dec. 2018
• SRM University Chennai, India
Bachelor of Technology in Information and Telecommunications July. 2015
Technical Skills
• Front-end Development: JavaScript,Typescript,Angular,Jquery, RxJS, HTML5 ,CSS3(Bootstrap,Angular Material)
• Programming Languages: Java (Spring/Spring Boot), Python (Numpy and Pandas), C# (ASP.NET)
• Database and Big Data Framework: Oracle, SQL Server,MySQL,MongoDB,Hadoop Stack (HDFS, Spark & Hive)
• Other Technologies: Oracle Data Integrator,Git ,Jenkins, R ,Jaspersoft ,Stata,MS Excel
Experience
• Raymond James and Associates St.Petersburg, FL
Application Developer Jan 2019 - Present
◦ Worked closely with capital markets and fixed income business users to develop 3 Angular web applications with
redux state management technique in an year which reduced their manual efforts by almost 50%.
◦ Implemented an authorization layer to the API’s with .net core in OWIN and subsequently developed changes in
the UI to pass the JWT token for each API request to authorize and set the user context.
◦ Responsible for API design and development of REST services in Java with spring boot and ASP.NET using entity
framework based on domain-driven design pattern and deployed using jenkins devops pipelines.
◦ Introduced performance enhancement techniques in Angular which improved the page load efficiency by 15% and
also optimized several complex SQL queries ,views, stored procedures and materialized views in oracle.
◦ Self Learned ODI and jaspersoft reporting tools to deliver business requirements in agile methodology.
Application Developer Intern May 2018 - Aug 2018
◦ Developed a Proof of concept in Angular 5 to rewrite existing legacy applications and research a real-time
notification system for client order entry systems using Atmosphere framework in Java and AngularJS.
• University of South Florida Tampa,FL
Research and Teaching Assistant Sep 2017 - May 2018
◦ Worked extensively in agile environment to develop production-ready web pages in Site Core CMS across USF .
◦ Performed data cleaning and modelling on the dataset which contained around 1 million instances and 75
attributes in Python and SAS EM respectively, followed by development of a visual dashboard in Tableau.
• Cognizant Technology Solutions Bengaluru, India
Programmer Analyst Sep 2015 - July 2017
◦ Migrated Cognizant’s Big Decisions web application from asp.net MVC with 12 new features in AngularJS and
improved security feature by executing token-based authentication using AngularJS, JWT & REST API.
◦ Developed a static website to present the designed tool to customers using HTML5, CSS, JS and Jquery.
◦ Worked in JIRA to track and eliminate the QA and security vulnerability issues in the built web application.
Projects
• The Effect of Image Choice on Airbnb reservations: This research project is a combination of deep learning and
econometric analysis presented at 4th Americas Conference on Information Systems (2018).It investigates how the
signals provided by airbnb hosts using images provided in the website, impact renting decision of guests. We conducted
an exploratory study by classifying images into categories using CNN deep learning model with airbnb listings data.
• Investigation of Error-resistant and Error-prone Messages : The aim of the project is to understand how error
messages are propagated over large-scale information networks and what content-related cues make certain error
messages more error-resistant or error-prone than others. The results of the project helped us build a web app that
accurately identifies errors by by determining ambiguity of a sentence using probabilities from stanford parser tool.