ML Engineer

# Optimization Engineer ## Company Overview (Company overview details not specified; section removed) ## Job Summary The Optimization Engineer will be responsible for refactoring and enhancing existing optimization logic to improve **speed**, **scalability**, and **modularity**. This role focuses on modeling price-volume relationships, developing constrained optimization techniques, and integrating business rules for effective scenario-based optimization. ## Responsibilities - Refactor and enhance existing optimization logic for improved speed and scalability. - Model price-volume relationships using elasticity inputs at the SKU (Stock Keeping Unit) and brand levels. - Develop optimization logic employing constrained techniques, including linear and quadratic programming. - Integrate business rules and constraints such as price bounds, SKU/brand-level caps, and TDP (Total Demand Potential) limits. - Enable scenario-based optimization with user-defined goals, such as maximizing profit or volume. - Support multi-brand optimization with no interdependencies between SKUs and brands. - Collaborate with cross-functional teams to validate model behavior and outcomes. ## Qualifications - Bachelor's or Master's degree in a relevant field (e.g., Mathematics, Statistics, Operations Research, Engineering). - Strong analytical and problem-solving skills. - Proficiency in programming languages, such as Python or R. - Experience with optimization libraries (e.g., Gurobi, CPLEX) for implementation of optimization techniques. - Familiarity with business rules integration and constraints modeling. - Ability to work collaboratively in cross-functional teams. ## Preferred Skills - Advanced knowledge of data analysis and statistical modeling. - Experience in financial modeling and price optimization. - Familiarity with Machine Learning techniques in optimization. ## Experience - 5 to 9 years of experience in optimization modeling, analytics, or related fields. ## Environment - Typical work setting details not provided; location and work type information are unspecified. ## Salary (Salary details not provided; section removed) ## Growth Opportunities (Career advancement opportunities not provided; section removed) ## Benefits (Benefits information not provided; section removed)