Decision Engine Development

From Rules of Thumb to Rigorous Models

Your team makes hundreds of decisions every week — pricing, targeting, resource allocation, risk assessment. Most of these rely on intuition, spreadsheets, or simple rules. They leave money on the table.

I build production-ready decision systems that encode domain expertise into probabilistic models. These systems don't just predict — they recommend optimal actions under uncertainty and tell you exactly how confident the recommendation is.

Applications

• →
  Churn Prediction: Identify at-risk customers before they leave, with calibrated probability scores and recommended interventions.
• →
  Pricing Optimization: Dynamic pricing models that maximize revenue or margin subject to demand elasticity and competitive constraints.
• →
  Ad Spend Optimization: Multi-channel budget allocation models that optimize spend across channels accounting for diminishing returns.
• →
  AI Recommendation Systems: Personalization engines that surface the right content, products, or actions based on user behavior patterns.

Predictive Model

A validated, calibrated model trained on your data with quantified uncertainty and performance benchmarks.

Decision Framework

Clear decision rules that map model outputs to concrete business actions with defined confidence thresholds.

Production-Ready Design

System architecture, API specs, and deployment plan ready for your engineering team to implement.