Summary

About

A programmer, developer, machine learning architect, and devops engineer, with over ten years of experience. Driven by a passion for programming, application development, machine learning algorithm design, natural language processing, and exploratory data analysis.

Technologies
  • Python: Polars, Pytorch, Sklearn, Numpy, Pandas
  • AI Frameworks: Ollama, HuggingFace, OpenAI
  • DevOps Frameworks: FastAPI, Flask, Asyncio
  • Cloud Services: Google Cloud Platform (GCP), AWS
  • Backend: Nginx, Linux infrastructure

Experience

MANAGER - MACHINE LEARNING & DATA SCIENCE || Oct 2020 to Present [Solo Dev] Developed and deployed a Propensity Model for Applications and Enrollments:
  • Methodology: trained a Neural Network on user-captured Google Analytics activity (clicks, time on site, etc)
  • Output: a Propensity Score for the likelihood that a client will Apply or Enroll
  • Backend: polars, pytorch, pandas, numpy, gcloudy
  • Frontend: BigQuery, Google Cloud Functions, Google Cloud Scheduler
[Solo Dev] Fine-tuned and deployed an in-house Large Language Model (LLM):
  • Methodology: fine-tuned a Llama3.1 model on Agent-Customer conversations
  • Output: Sentiment, Summary, and Deep-Dive Analytics of spoken conversations between Agents and Customers
  • Backend: Ollama, polars, pytorch, numpy, pandas, gcloudy, verba, Retrieval-Augmented Generation (RAG)
  • Frontend: Ollama, BigQuery, Google Cloud Functions, Google Cloud Scheduler
[Solo Dev] Developed and deployed an Enrollments Forecast Model:
  • Methodology: developed 'RandomRiver', a custom decision-tree algorithm, and applied it to historic enrollment data
  • Output: a Forecast of Enrollments on a by-Day and by-Site resolution
  • Backend: polars, pytorch, numpy, pandas, gcloudy, verba
  • Frontend: BigQuery, Google Cloud Functions, Google Cloud Scheduler
DevOps / Management:
  • Admin of our team’s Google Cloud Project, managing server maintenance, permissions, users, and IAM
  • Directed cooperation between Google Cloud Platform services (BigQuery, Cloud Functions, Cloud Scheduler, etc)
  • Created all API frameworks with connections to platforms such as Google, Meta, TheTradeDesk, and Invoca
  • Developed all production level microservices and frameworks for our team
  • Implemented department-wide version control protocol using Git and Google Source Code
  • Managed IAM, permissions, and authorizations for entire department and contractors
  • Provisioned and curated all VMs and servers

MACHINE LEARNING ARCHITECT || Apr 2019 – Feb 2020 Machine Learning / AI:
  • Worked entirely within the Amazon AWS Cloud Infrastructure, utilizing many AWS Services
  • Developed a Deep Learning ML Model predicting rare-events data using R and H2O
  • Designed a Hypertuned Ensemble Stack Model using R and H2O for unbalanced data
Dev Ops / API:
  • Developed an R Package for server-side interface with tables stored in Redshift Spectrum
  • Launched and managed a Linux-based R-Server and developed an integrated monitor app via Shiny
  • Developed an Alteryx pipeline comprising of Redshift Spectrum input and S3 output
  • Assisted in database implementation of Redshift and Redshift Spectrum table objects
  • Experience in Microservice App Deployment using AWS Lambda, Terraform, and Python
  • Worked on REST API integration from an SAP database
  • Agile project task management using Jira
  • Version control using Git in AWS CodeCommit

SENIOR ASSOCIATE, FP&A || Sep 2016 – Jul 2018
  • Developed a Random Forest Algorithm in R for quarterly and annual business planning
  • Developed Time-Series Models in R for financial & supply-chain forecasting
  • Developed a User Interface (UI) for the forecast model using R, Shiny, and Javascript
  • Dashboard development including Key Performance Indicators (KPI) and BI Analytic