About
I'm a software engineer and grad student. Most of my work sits somewhere between backend engineering and data science — building APIs, wiring up data pipelines, and getting ML models into production.
Right now I'm finishing my Master's in Computer Science at Seattle University, focused on Data Science. Day to day, that means a lot of Python, Django, AWS, and Docker.
Before this, I worked as a Quantitative Research Analyst where I built data pipelines that handled 50,000+ market records and forecasting models that cut manual analysis time by 40%. I've also done web development and graphic design work.
When I'm not coding, I'm usually exploring Seattle's coffee spots, messing around with new datasets, or reading up on whatever's new in AI.
Skills
Languages & Tools
Frameworks & Libraries
Cloud & Data
Experience
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Jul — Oct 2023
Quantitative Research Analyst Intern · Finkey Consultancy
Built automated data pipelines with Python and AWS Glue to process 50,000+ market records, cutting data retrieval time by 45%. Also built dashboards and ARIMA forecasting models that saved portfolio managers about 40% of their manual analysis work.
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May 2023
Student Ambassador · Internshala
Ran marketing campaigns that pushed internship applications up by 24%. Figured out what messaging worked for different student groups and scaled it.
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Jan 2020 — Jan 2023
Web Developer & Graphic Designer · Vikasana Inc.
Built websites alongside designers and content teams. Also handled visual design for events and social media to help grow the brand's online presence.
Projects
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EraEx — Vibe-Driven Music Recommendation
Music discovery engine built for SoundCloud's 2013-2018 era. You describe a mood, and it uses FAISS vector search and cross-encoder re-ranking to find relevant tracks from 14M+ entries in under a second.
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DreamScope — Offline Dream Analysis
Record your dreams right after waking up. The app transcribes them offline with Vosk, pulls out themes, emotions, and keywords through NLP, then layers in weather and moon phase data to spot patterns.
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PhishNinja — Phishing Detection System
Flask web service that classifies malicious URLs in real time with 92% accuracy. Built with a clean MVC architecture and shipped in Docker for easy deployment.
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BFloat16 Fraud Detection
Compares float32 and bfloat16 precision for training fraud detection neural networks. Uses SMOTE to handle class imbalance. The goal: see how much you can reduce precision without hurting accuracy.
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Child Nutrition Tracking App
Full-stack app built with Django REST and React. Has 8+ API endpoints secured with JWT, a PostgreSQL backend, and a Scikit-learn model that processes health data at 89% accuracy with sub-200ms response times.
Education
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Sep 2024 — Mar 2026
Master of Science in Computer Science · Seattle University
Focused on Data Science — machine learning, data systems, and statistical modeling.
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Mar 2020 — Jun 2024
Bachelor of Technology in CS & Engineering · Presidency University
Focused on AI and Machine Learning. Published a research paper on deep learning-based detection systems. Placed 2nd at the REVA University Hackathon.
Certifications
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2025
AWS Cloud Solutions Architect
Coursera / Amazon Web Services
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2026
Google Advanced Data Analytics
Coursera / Google
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2026
IBM Data Science Professional
Coursera / IBM
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2026
IBM AI Developer
Coursera / IBM