ML OPs Engineer – Pricing Optimizer Development

Role Overview

We are looking for a skilled ML Engineer to design and build a robust, interpretable, and scalable optimization engine that enables data-driven pricing decisions. The engine will leverage SKU-level demand, elasticity, and profitability data to recommend optimal pricing strategies based on business goals.

Key Responsibilities

• Refactor and enhance the existing optimization logic for speed, scalability, and modularity.
• Model price-volume relationships using elasticity inputs at SKU and brand levels.
• Develop optimization logic using constrained techniques (e.g., linear / quadratic programming).
• Integrate business rules and constraints such as price bounds, SKU / brand-level caps, and TDP limits.
• Enable scenario-based optimization with user-defined goals (e.g., maximize profit or volume).
• Support multi-brand optimization without interdependency between SKUs and brands.
• Collaborate with cross-functional teams to validate model behavior and outcomes.

Inputs You'll Work With

Deliverables

Tech Stack & Skills

Skills Required

Python, Numpy, Pandas, Scipy