Data Scientist
- Developed flight-phase classifiers served through a query-on-demand dashboard for recorded aircraft telemetry
- Built operational analytics workflows over externally ingested telemetry for flight-performance monitoring
- Delivered REST APIs exposing machine learning models and engineering analytics to operational systems
Flight data monitoring case study →
Machine Learning Engineer
- Developed predictive machine learning models for vending-machine delivery-failure forecasting using large-scale transaction and telemetry data
- Performed exploratory and statistical analysis to identify patterns affecting system performance and operational reliability
- Built data-processing and KPI-monitoring workflows to support data-driven operational decisions
Operational Data Analyst
- Optimised SQL queries and automated recurring reporting workflows for business-intelligence systems
- Developed reproducible data-processing workflows and transformed operational data into actionable performance metrics
Digital Engineering Intern
- Developed computational-geometry algorithms for engineering simulation and finite-element meshing workflows
- Improved data-structure operations for tire cross-section geometry processing and implemented closest-point algorithms for cubic Bézier curves
Machine Learning Intern
- Implemented an InsetGAN architecture for whole-body human-image generation and developed the associated deep-learning inference workflow
- Deployed model inference through FastAPI for integration with a Swift iOS application
Independent engineering work
Alongside my professional work, I developed an aircraft engine audio-monitoring prototype using Raspberry Pi, FFT-based signal processing, and an ESP32 display. This personal project is separate from the Intuos telemetry dashboard.