Career

Experience

Santech logo

Data Scientist & Software Engineer

Santech

Nov 2025 — Present

First data hire at an early-stage IoT startup — building the product, the pipeline, and sometimes packing the truck.

  • Building a full-stack dashboard (React + .NET + InfluxDB + Grafana) to turn raw vibration data into equipment health signals
  • Owning the data pipeline end-to-end: Modbus TCP ingestion, Node-RED flows, time-series storage, AI-driven anomaly detection
  • On-site when needed — coordinating installs, validating sensors, making sure the data that comes in actually means something
Walmart logo

Software Engineer — Contractor

Walmart

Jun 2025 — Aug 2025

Embedded on the Glass platform team keeping the Walmart Android app running for tens of millions of users.

  • Refactored startup initialization from eager to lazy loading in Kotlin — a small change with a measurable footprint reduction at scale
KGS Technology Group logo

Data Engineering Consultant

KGS Technology Group

Dec 2024 — Jun 2025

Built the data layer for a manufacturing client putting sensors on the factory floor for the first time.

  • Designed ingestion pipelines to pull sensor telemetry off plant equipment and land it in structured tables for downstream use
  • Bridged the gap between plant ops and data infrastructure — translating physical signals into queryable, reliable data
American Airlines logo

Digital Analytics Analyst

American Airlines

Feb 2024 — Nov 2024

Promoted from intern to full-time on the Digital Analytics team, owning customer satisfaction intelligence for leadership.

  • Dug into NPS and CSAT data to find the real story — separating causation from correlation across loyalty tiers, routes, and promotions
  • Turned ambiguous score drops into concrete narratives that shaped how executives prioritized CX investments
American Airlines logo

Data Science Intern

American Airlines

Sep 2023 — Dec 2023

Started in the Operations Research & Advanced Analytics group, where the work converted into a full-time offer.

  • Built a CatBoost model to predict Likelihood to Recommend scores and connect them to business KPIs
  • Used SHAP to explain what actually drives customer loyalty — and tuned the model output to align with how the business thinks, not just how it scores