Nicholas Sliter
Lead Machine Learning Engineer
I work on large-scale machine learning systems that drive real-world business impact, spanning personalization, forecasting, experimentation, predictive and prescriptive analytics, profitability optimization, audience segmentation, fraud detection, and more.
I enjoy turning raw, messy data into reliable signals and features, and building systems that consistently extract real value from it in production.
Focus Areas
- Designing and owning large-scale ML systems from problem framing through production and iteration
- Personalization, recommendation systems, and audience segmentation at scale
- Forecasting, optimization, and prescriptive analytics for business and operational decisions
- Demand and labor forecasting systems supporting planning, staffing, and operational efficiency
- Experimentation platforms, causal inference, and measurement strategy
- Applied ML for fraud detection, identity resolution, and risk mitigation
- Technical leadership across teams
Background
Previously studied computer science and mathematics at Middlebury College.