Decision Scientist (Operations Research)

Optimization models, LP/MIP and duality

Coverage: Mathematics for Data Science / Decision Science

• ▶Introduction to Linear Programming — MIT OCW
• ▶Duality in Linear Programming — MIT OCW

Probability, estimation and uncertainty

Coverage: Statistics & Probability

• ▶Classical Statistical Inference I — MIT OCW
• ▶Parametric Inference INTERMEDIATE Simulate uncertainty + establish causal and forecast evidence — MIT OCW

Simulation, sensitivity and scenario analysis

Coverage: Forecasting & Decision Science

• ▶Monte Carlo Simulation — MIT OCW
• ▶Monte Carlo Simulations — MIT OCW

Causal inference, experiments and forecasting

Coverage: Causal Inference / Forecasting

• ▶Causal Inference, Part 1 — MIT OCW
• ▶Time Series Analysis — MIT OCW

Decision systems, solver workflows and validation

Coverage: Python / APIs / Decision Engineering

• ▶Build, Test & Deploy an OR-Tools MIP Model — Nextmv
• ▶OR-Tools Decision Workflows & Scenario Testing — Nextmv

Executive decision communication and adoption

Coverage: Data Storytelling & Visualization

• ▶Visualizing Data — MIT OCW
• ▶How to Turn Data into Stories — storytelling with data