Nicole Misek

VP of Decision Engineering
Nicole is VP of Engineering at Nextmv. Previous to Nextmv, Nicole worked as a statistician at Grubhub where she helped the scheduling, dispatch, and market management teams improve their systems. Outside of work, Nicole spends most of her time chasing around her two toddlers and keeping them from getting into too much trouble.
Link and test logistics models for demand forecasting, shift scheduling, and vehicle routing

Follow this step-by-step tutorial to go from a forecasted demand to optimized routes for delivery and similar use cases. Create and customize decision apps using OR-Tools, HiGHS, Pyomo, and more.

What is switchback testing for decision models?

It’s time to understand the behavioral impacts of a new decision model under real-world conditions compared to a production model. Switchback testing enables this, helping build confidence in a new model’s rollout in a safe and measured way.

Create optimized PagerDuty on-call rotation schedules with decision automation

I retired our on-call scheduling spreadsheet — and you can too. Here’s how I built a custom decision model that generates and sends optimized schedules to the PagerDuty API.

Optimization modeling with AMPL, Streamlit, and Nextmv: A stochastic facility location example

Create robust and interactive decision apps with AMPL as the optimization layer, Nextmv as the DecisionOps layer, and Streamlit as the UI and visualization layer. Learn how with a facility location example.

Comparing decision models in operational environments with switchback testing

When you’re ready to have a candidate model make true operational decisions, it’s time for switchback testing. Kick off an experiment and analyze how your new decision model measures up to your current model in production.

Best practices for customizing your model in 30 minutes

With Nextmv, you can customize an optimization model for your use case without wading into linear inequalities. From creating your own value function to adding custom constraints, learn best practices for representing business logic as code.