Software professional with 7+ years across Software Engineering, Test Automation & Data Analysis — crafting automation solutions for Fortune 500 clients. Currently advancing my expertise in Data Analytics & Engineering at Northeastern University.
// developer profile
const akash = {
name: 'Akash Ghosh',
role: 'Software Engineer',
location: 'New York City',
experience: 7,
stack: [
'Java', 'Python', 'C#',
'SQL', 'AWS', 'React'
],
currentlyLearning: 'ML & Analytics',
passion: 'Building things'
};I'm a passionate software professional based in New York City, working at the intersection of engineering, automation, and data.
Over the past 7+ years, I've architected test automation frameworks and built systems for industry leaders like JP Morgan, Wells Fargo, and Bank of America. My work spans test automation engineering, software development, and data analytics — using tools like Selenium, Playwright, Cypress, and AI-assisted testing with GitHub Copilot and ChatGPT/Claude.
Currently pursuing my MS in Data Analytics and Engineering at Northeastern University (graduating August 2026), I'm bridging traditional software engineering with modern data science—building systems that don't just work, but learn and adapt.
Architecting test automation frameworks for JP Morgan, Wells Fargo, and Bank of America. Integrating AI-assisted tools for intelligent test generation.
Built CI/CD pipelines and data quality validation in an Agile startup environment.
Delivered 3 short-term software analysis projects for financial systems.
Built robust validation frameworks in fast-paced Agile sprints.
Designed automation infrastructure for major banking platform.
Full-stack travel journal with interactive maps. Users log trips, add photos, and visualize their travel history with geolocation.
Cloud-native data pipeline for real estate price prediction. Integrates Zillow data with US Census demographics through AWS services.
Machine learning models for stock price forecasting. Applied regression algorithms and time series analysis to predict market patterns.
Predictive ML analysis on US housing market trends and pricing factors. Applied regression models to forecast home values across regions.
PostgreSQL database design for insurance management with normalized schema, ETL processes, and OLAP data warehouse for business analytics.
Time series analysis for human activity recognition using sensor data. Implemented LSTM neural networks for pattern detection and anomaly identification.
Want to see more? Check out my complete portfolio on GitHub.
View All RepositoriesI'm always open to discussing new opportunities, interesting projects, or just having a conversation about technology.