Updated - 6th Feb

1. Shubham Mehta
Ph. No: 480.543.9520 | Email: shubhamrishimehta@gmail.com | Website: http://shubham-mehta.com/
SUMMARY
Curious, Result-Oriented, Techie aspiring to craft an impactful career in a Modern, Data-Driven Software Organization. 4+
years of industry and research experience using Java, Python, C++, C#, JavaScript, AWS Lambda, Qlik Sense, and RPA.
EDUCATION
Major: M.S., Computer Science (Big Data Systems) Cumulative: 3.71/4.00 GPA Graduated May 2021
Major: B.S., Computer Science Minor: Business Cumulative: 3.84/4.00 GPA Major: 3.96/4.00 GPA Graduated May 2020
Arizona State University, Tempe, AZ
TECHNICAL SKILLS
Programming: Java, Python, R, C#, C++, JavaScript, React, C
Tools/Technology: AWS, Hadoop, PostgreSQL, Kafka, Excel, Tableau, SQL, MS SQL Server, RPA, Spark, Node.js, Oracle, Linux
INDUSTRY EXPERIENCE
Amazon, Software Development Engineer (Tempe, AZ) 06/2021 – Present
● Designed & implemented a retry queue strategy for huge SQS messages which improved the latency and memory
usage by 14% for 2 of our team's ARest microservice.
● 3 million+ seller feature development for calculating accurate Account Health Rating for 3rd party sellers in
Amazon.com on their Account Health Dashboard in Seller Central.
● Developed a Native AWS application from an Apollo environment with an auto-scaling group in it which serves 48
clients with 68 total APIs.
DHL Global Forwarding, Solution Delivery Intern (Tempe, AZ) 06/2020 – 04/2021
● Built a dashboard in Qlik Sense that directly led to process efficiency gains of 35%. Generated insights for company
warehouses which helped the DHL team to improve the inbound/outbound process of shipments for customers.
● Automated Invoice systems for DHL customers in North America by creating an RPA application.
● Implemented innovating IoT solutions that helped to improve security and operational aspects of DHL Warehouses.
RESEARCH EXPERIENCE
ASU, Cubic Lab, Undergraduate Researcher (Tempe, AZ) 05/2018 – 05/2020
Emotional Response to Vibrotactile and Thermal Stimulation | Publication
● Led research efforts on a groundbreaking project funded by the NSF to modernize human-machine interaction via
optimal application of thermal and vibration patterns to the human body.
● Team Lead – Designed Research Methodology. Developed Java application and Python Scripts to collect and store
Real-time user responses. Modeled, transformed, and analyzed data to drive meaningful Insights recognized by NSF.
Indoor Localization for Navigational Aids (FURI) | Link
● Team Lead - Improved indoor living for vision-impaired people. Collaborated with Intel's Responsive Retail Platform
and SpotSense to develop an Ionic-based navigation app with Open CV, used to track objects using RFID tags.
● Made new skills in Echo Dot using AWS Lambda to help in Indoor Navigation with the help of Bluetooth beacons.
OTHER PROJECTS
Visualization Popular Restaurant | Link 05/2020 – 07/2020
● Built a Real-Time recommendations application for best food choices in Tempe, based on current time & day of the
week.
● Used Yelp dataset (10 years) and manipulated the data in Tableau using D3.js, HTML, SVG, and CSS to help visualize it
geospatially and in various other intuitive representations.
Automatic Tagging of Medical Texts 08/2019 – 05/2020
● Created a program to automate highlighting medical terms in order to help doctors improve the accuracy of their
diagnoses. Built a RESTful API for the JavaScript frontend to communicate with the Python backend.
● Worked on ML algorithms to process big data sets and integrated NLP to associate similar words and phrases.
Real Estate Price Prediction | Link 06/2020 - Present
● Created a model which predicts the price of an apartment using sklearn, linear regression & other DM techniques.
● Building a web application for users using Python, flask for HTTP server, and HTML/CSS/JavaScript.
Ace It, Chrome Extension (1st
Place @SunHacks Hackathon) | Link 11/2018
● Built a Chrome Extension using JavaScript to de-obfuscate blocked content on a solution website by cross-referencing
a database of existing solutions and replacing the obfuscated content with the discovered data which helps students.