I'M
shREYASIS ROY.

BRIDGING TECHNOLOGY & BUSINESS for IMPACTFUL SOLUTIONS

01 EXPERTISE

MY KNOWLEDGE LEVEL IN SOFTWARE

JAVA

95%

SQL

80%

85%

BLENDER

75%

PYTHON

80%

JAVASCRIPT

85%

LLM

80%

REACT

80%

AWS TECH

80%

SOLUTION DESIGN

85%

PRODUCT MGMNT

75%

PROFESSIONAL

Dynamic Software Development Engineer (SDE) with over 5 years at Amazon, specializing in scalable solutions that enhance user experience and operational efficiency. Proven track record in leading cross-functional teams and driving projects that boost productivity by up to 50%. Certified in Product Management from Stanford University, blending technical expertise with strategic product vision to deliver user-centric solutions

02 PORTFOLIO

MY LATEST WORK (AS A HOBBY). SEE MORE >

03 Experience

September 2022 - Present

SDE - II @ AMAZON

Software Development Engineer

Unified Knowledge Base Architecture: Led the design and implementation of a centralized knowledge repository leveraging Large Language Models (LLMs), increasing internal developer productivity by 50%.
Cross-Functional Collaboration: Coordinated with product managers and third-party vendors to deploy product changes, ensuring alignment with business objectives and timely delivery.

Jul 2020 - August 2022

SDE - I @ AMAZON

Software Development Engineer

Amazon SellerCentral Navigation Redesign: Spearheaded the navigation redesign, resulting in a 25% increase in customer satisfaction and a 30% reduction in latency.
Leadership and Mentorship: Guided junior engineers, fostering a collaborative environment and promoting adherence to Amazon's leadership principles.

Jan 2020 - Jul 2020

SDE INTERN @ AMAZON

Software Development Engineer Intern

Big Data Handling: Developed solutions for big data processing using Dryad Pipelines and AWS Lambda, enhancing data processing efficiency for the VAT International Sellers Team.

2019-2020

HACK-HARVARD FINALIST

2nd Runner-up at HackHarvard Global 2019 - 2020

Awarded 3rd place for conceptualizing and developing EdEasy, a mobile-first platform designed to provide underprivileged students with personalized learning pathways.
Leveraged Machine Learning algorithms to analyze student data and recommend tailored courses to optimize learning outcomes.
Collaborated with a cross-functional team to pitch the project to tech leaders from Google Cloud and Facebook, earning accolades for innovation and impact.
Demonstrated exceptional teamwork and technical skills, building a scalable MVP within 36 hours.

May 2019- July 2019

ML INTERN @ CONDUENT

Machine Learning Engineer Intern

Developed a Crime Prediction Analyzer with a custom Machine Learning pipeline to identify crime hotspots.
Published a recognized research paper on the methodology, accepted by Conduent for practical impact.
The solution is used by crime organizations in regions like Denver to support law enforcement in targeting high-risk areas.
Improved geographic data analysis by integrating predictive models into QGIS for public safety initiatives.