Ottawa, Canada | Data Scientist | Ph.D. Earth Science

Production AI for complex, high-stakes data.

I design and ship machine learning systems across enterprise NLP, LLM and RAG workflows, forecasting, remote sensing, and multimodal sensing programs.

  • 400M+ records supported in large-scale classification programs
  • POC to Prod delivery across prototyping, orchestration, and production rollouts
  • NLP to Sensing experience spanning text, forecasting, vision, and multimodal ML

Focus areas

Built for enterprise delivery, research rigor, and field constraints.

My work sits at the intersection of production engineering and model development: problem framing, data pipelines, evaluation, deployment, and iteration.

01

Enterprise NLP Systems

Hierarchical classification, sentence-transformer fine-tuning, active learning, and scalable inference for messy real-world text.

02

LLM and RAG Workflows

Grounded generation, retrieval design, evaluation frameworks, and citation-aware reporting for decision-support use cases.

03

Forecasting and Optimization

Multivariate demand forecasting, pricing signals, anomaly detection, and repeatable Databricks + MLflow pipelines.

04

Computer Vision and Sensing

Remote sensing, object detection, and multimodal fusion for UAV and satellite workflows that have to work outside the lab.

Selected impact

Recent programs, described at the problem level.

Client-facing engagements are intentionally generalized here so the site shows the work without exposing unnecessary delivery details.

Retail modernization

Large-scale taxonomy automation

Built hierarchical NLP classification and active-learning workflows that supported automation across hundreds of millions of product records.

LLM systems

Grounded briefing generation

Designed retrieval and evaluation pipelines for structured, citation-aware report generation from free-form source material.

Aviation analytics

Forecasting and pricing decision support

Combined utilization, maintenance, supplier, and failure signals into demand forecasting and elasticity modeling workflows.

Multimodal sensing

Field-ready low-contrast detection

Implemented EO, IR, GPR, and magnetometer fusion pipelines for operational detection tasks where single-sensor approaches were not enough.

Selected work

Applied AI case studies and research tooling.

Browse all projects

Project 6

QuakeLabeler

Seismic annotation and dataset creation toolbox for AI-ready earthquake research.

Experience snapshot

Built from research depth, delivered in production settings.

2023 - Present

Data Scientist

Larus Technologies | Ottawa, Canada

Build and deploy applied AI systems across enterprise, aviation, defence-adjacent, and sensing programs.

Selected engagements

Contributor and Reviewer

Outlier AI | Remote

Evaluated frontier AI models in mathematics and physics using research-grade prompts, rubrics, and failure analysis.

2019 - 2023

Ph.D. Researcher, Earth Science

University of Ottawa | Ottawa, Canada

Built open-source ML tooling for earthquake detection, denoising, phase picking, and seismic dataset creation.

Publications

Selected research outputs.

See the full publication list

Contact

Open to applied ML, platform, and research-heavy AI work.

If the problem involves ambiguous data, operational constraints, or model delivery beyond a notebook, that is usually where I am most useful.