Dhanish Parimalakumar

Data Scientist focused on production machine learning, credit risk modeling, experimentation, and business-facing analytics. Graduated from The University of Texas at Dallas with a B.S. in Data Science in May 2026, with experience spanning production ML, dealer analytics, statistical modeling, automation, and full-stack AI products.

Experience

Data Scientist I

GoFi / DriveTime

Jul 2026 – Present Dallas, TX Production ML

Building production vehicle recovery models and a VIN-based API for real-time recovery estimation.

Data Scientist Intern

GoFi / DriveTime

May 2025 – Jul 2026 Dallas, TX Credit ML

Built credit-risk models, scoring workflows, dashboards, and dealer analytics, including a production XGBoost model across 1.2M applications.

Network Engineering Intern

Verizon

Jun 2024 - Aug 2024 Dallas, TX Automation

Automated capital budget reporting and supported server-side reporting handoff.

Undergraduate Research Assistant

UT Dallas, VIEWS Project Lab

Aug 2023 - May 2024 Richardson, TX Forecasting

Developed statistical models for political violence fatality forecasting.

Projects

Automate Chess

Real-time multiplayer chess auto-battler with server-authoritative matches and Stockfish simulation.

  • React
  • FastAPI
  • WebSockets
  • Stockfish
  • Docker

Controlled Agricultural Environment Simulation

Private Built as a proprietary application for a corporate sponsor.

Physics-based growroom simulator for estimating energy demand from sensor and weather data.

  • Python
  • Simulation
  • Sensors
  • Energy Modeling

Agentic AI product-planning tool that transforms sketches and text ideas into structured technical plans through multi-step LLM workflows.

  • Next.js
  • TypeScript
  • Supabase
  • NVIDIA NIM
  • LLM Workflows

Bitcoin Price Prediction with LSTM

NumPy-only LSTM from scratch for next-day Bitcoin prediction with chronological validation and a trading simulation.

  • Python
  • NumPy
  • LSTM
  • Time Series

Interests

Outside of work, you’ll usually find me optimizing a gaming strategy, chasing a cleaner lap at autocross or the track, hiking or camping when I can, and window-shopping watches I can’t justify buying (yet).