Resume

Built an Amazon Neptune (openCypher) knowledge graph linking 2M+ pets, prescriptions and products, then piped it into a KG + LLM vet-assistant that slashed per-rx review time from 10 to 1 min and cut backlog from 75h to <6h (~92%). Trained a 91-% precision rx quality classifier and auto-generated "approve/fix/why" summaries, trimming vet follow-ups by 70% and streamlining bulk approvals in Chewy Pharmacy.

Spearheaded the development of a farming companion app, with an XGBoost-powered recommendation system using Flutter, FarmOS and Python, cutting resource usage by 35% and boosting productivity by 20%. Designed features for task tracking, data analysis and actionable insights to empower farmers. Analyzed pilot farm user behavior to build a community database and AI/ML models tailored for agriculture.

Developed an OCR solution to automate retail product labelling, data processing, creating a query-able inventory database for 5000+ products across 100+ stores. Designed and implemented an end-to-end full-stack solution - a web-based GUI using Django and Python, enabling non-technical users to query and configure product data.

Led strategic development of a fintech product roadmap and business case for a fractional investment platform in precious metals, expanding access to financial markets for underserved populations resulting in a product with 5K+ downloads and 200+ monthly active users since release in October 2022.

Coursework: Deep Reinforcement Learning, ML with Graphs, Generative AI, Advanced Natural Language Processing, Intro to Deep Learning, ML in Production, AI Venture Studio, AI Commercialization, Comp. Tech Law, Intro. to Computer Systems

Relevant Coursework: Data Structures & Algorithms, Computer Organization, Database Management Systems, Distributed Computing