Hi, I'm Shashank 👋
Software Engineer | Data Scientist
SHS

About

I am a software engineer with a strong background in data science and machine learning. I have experience in building scalable applications and deploying them using modern technologies. I am passionate about solving complex problems and continuously learning new skills.

Skills

Java
Spring Boot
Typescript
Python
PostgreSQL
Docker
Kafka
PyTorch
Pandas
REST
gRPC
Microservices
My Projects

Check out my latest work

Patient Management System

Patient Management System

Built a microservices-based patient management system using Spring Boot, Kafka, gRPC, and an API Gateway. Deployed with Docker on Railway, it demonstrates event-driven communication between services like patient, billing, and analytics, while the API Gateway orchestrates requests and handles service routing.

Java
Spring Boot
PostgreSQL
Docker
Kafka
gRPC
Microservices
API Gateway

E-commerce Sales Dashboard

Built an interactive E-Commerce Sales Dashboard to help store managers analyze sales performance, regional trends, and fulfillment methods. Designed for data-driven decision-making, it transforms raw sales data into actionable insights.

Python
Dash
plotly
pandas
pysorting: A Python Package for Sorting Algorithms

pysorting: A Python Package for Sorting Algorithms

Developed a Python package that offers an interactive platform to explore and understand popular sorting algorithms. Designed for students and educators, it features customizable implementations of key sorting algorithms, making it an excellent tool for both learning and teaching sorting concepts.

Python
Pytest
Poetry
CI/CD
Hackathons
  • W

    WiDS Case Competition

    Vancouver, BC

    Developed a regression model in Python using XGBoost to predict monthly revenue for Airbnb listings by leveraging feature engineering, TF-IDF text processing, and hyperparameter tuning, achieving 1st place in the private kaggle competition.
Contact

Get in Touch

Want to chat? Just shoot me a dm on Linkedin or email me and I'll respond whenever I can.