I recently completed my M.S. in Computer Engineering at New York University, where I also worked as a Data Analyst and Salesforce Admin at the NYU K12 STEM Education Center.
My work sits where analytics, backend engineering, and applied ML meet. I enjoy building systems that are useful in the real world: tools that catch risky cloud defaults, workflows that surface fraud signals, dashboards that help people make decisions, and open-source fixes that improve platform behavior.
I care most about engineering that is practical, explainable, and production-minded.
- Cloud security tooling for finding risky defaults before deployment
- ML-backed data systems for fraud detection, scoring, and decision support
- Open-source engineering across workflow and finance platforms
- Dashboards and operational analytics that turn raw data into action
|
A Terraform plan scanner that detects security-relevant omitted defaults before they quietly reach production.
Stack: Python, Terraform, CLI, AWS security rules |
An end-to-end fraud detection system for large-scale credit card transaction analysis.
Stack: PySpark, MLlib, Flask, Pandas, React |
|
A full-stack application covering books, events, study rooms, invoices, and role-based access.
Stack: React, JavaScript, SQL, MySQL |
I like contributing where the problem is concrete and the fix improves actual developer workflows.
|
Beyond repositories, I also spend time helping in public technical communities.
- Contributed fixes and improvements to Apache Airflow
- Contributed validation and localization updates to Apache Fineract
- Shared accepted solutions on Cisco Community in routing, switching, and network security discussions
Languages
Frameworks and Data
Cloud and Engineering
- Portfolio: siddharthanps.info
- LinkedIn: ssiddharthan
- Medium: @siddharthanps.1
- Cisco Community: public profile
- Email: sp8004@nyu.edu