Eugene Ayonga

MS. Data Science | University of Rochester

Generative AI Data Scientist

AI Agents Business Intelligence Computer Vision Deep Learning LLMs Machine Learning NLP

About Me

I'm a founder and Generative AI Data Scientist with an MS in Data Science from the University of Rochester. I specialize in building intelligent systems that combine data engineering, machine learning, and generative AI to solve complex problems across healthcare, technology, and business in both public and commercial sectors. My experience spans designing end-to-end data and AI solutions; from scalable data pipelines on AWS and PySpark to deep learning and LLM applications for language, vision, and autonomous agents, including RAG chatbots and AI agents for automated market research.

I'm passionate about turning complex data into clear, actionable insights that deliver measurable impact. Through a portfolio of projects and my venture, Vesnay, I seek to leverage technical depth and cross-domain insight to drive data-informed decisions and build intelligent systems that learn, adapt, and create tangible value.

22 Projects
MS Data Science
3 Published Research

Featured Projects

Research & Publications

Professional Experience

Founder & CEO

Vesnay Nov 2025 - Present
  • Founded VESNAY, an AI wardrobe OS using multi-agent LLMs and concierge workflows to plan outfits by calendar, city, and climate
  • Curated product vision, value proposition, and go-to-market for bespoke, luxury wardrobe management for high net worth individuals
  • Built the MVP using React Native, Supabase, and agents to ingest wardrobe, weather, and calendar data and generate recommendations
  • Built wardrobe graph and recommendation logic to learn each user's rhythm across homes, and seasons to surface context-aware looks
  • Identified three prospective pilot users and planned discovery to refine workflows, pricing, and engagement KPIs

Data Scientist

City of Rochester - Fire Department Aug 2024 - Dec 2024
  • Architected comprehensive data analytics solution processing 1.2M+ emergency incident records using Python, SQL, and PySpark to optimize emergency response resource allocation and deployment strategies
  • Developed high-accuracy time series forecasting models achieving 0.85 R² score using Prophet and SARIMA, enabling 10-year demand projections to inform strategic capital planning and staffing decisions
  • Delivered data-driven recommendations projected to save $800K+ annually through optimized station locations, equipment distribution, and personnel scheduling based on geospatial and temporal demand analysis
  • Presented actionable insights and interactive Tableau dashboards to Fire Chief and city stakeholders, translating complex statistical findings into executive-level recommendations for emergency services optimization
  • Co-authored research report "Improving Emergency Response Performance at the City of Rochester Fire Department" (2024)

Data Science Intern

OpenBrand Jun 2024 - Dec 2024
  • Engineered cloud-based business intelligence infrastructure for consumer products on AWS, deploying real-time dashboards in QuickSight that automated KPI tracking and reduced manual reporting time by 70%
  • Designed and implemented Python-based dynamic pricing calculator leveraging machine learning algorithms, directly generating $4,000+ in cost savings and improving pricing strategy accuracy
  • Conducted comprehensive market analysis using SQL and statistical modeling to identify consumer behavior patterns, informing product positioning strategies that enhanced competitive market intelligence
  • Communicated complex analytical insights to C-level executives and cross-functional stakeholders through compelling data visualizations and presentations, driving strategic business decisions across marketing and operations teams

Technical Skills

Programming & Data Science

Python
SQL
PySpark
R

Machine Learning & AI

Scikit-learn
TensorFlow
PyTorch
Hugging Face

Tools & Platforms

AWS
Databricks
Docker
Git

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