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Gabriel Undrerwood
Engineering executive specializing in production ML systems and enterprise SaaS
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Engineering/data platform leader from FLYR (airline ML forecasting and automated pricing) who built scalable ingestion/ETL and a canonical data model to onboard airlines with highly heterogeneous source systems. Created a golden-metrics layer for airline KPIs and implemented monitoring/backfill capabilities, cutting onboarding time by 50%+ while improving SLA performance and controlling cloud/ML training costs through stronger data quality gates.
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Key Strengths
- Built canonical data model + data platform enabling generally-available features across diverse airline customer data sources
- Reduced customer onboarding time by over 50% via ETL tooling, operational capabilities, and onboarding playbook
- Established golden KPI/metrics team to standardize business logic and prevent inconsistent downstream analytics/ML features
- Implemented robust data ops (freshness/quality monitoring, alerts, backfills) to improve reliability and speed find-fix-test cycles
- Scaled engineering org alignment with Program Review/Scrum-of-Scrums including Product, Sales, and Customer Success to manage dependencies and priorities
- Led major data model migration (natural key to synthetic key) coordinating changes across R&D and BI; improved performance, inference SLAs, cloud spend, and developer velocity
- Drove cloud cost reduction by tightening data quality gates before repeated ML training cycles
- Strong operating cadence and meeting/decision hygiene (right attendees, action items, architecture reviews with pre-reads)
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1 publication
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