This is a fully remote position, open to applicants in Argentina.

📋 Description

• Mathematically formalize the trade-off between service time, RTM cost, and revenue for each point of sale, developing the optimization function that currently operates on a heuristic basis.

• Create a model for the cost and profitability layer (visit drivers, RTM size thresholds, minimum margin) that informs segmentation and service model assignments.

• Construct and solve optimization models (linear/integer programming, constrained optimization) to identify the optimal service model for each client.

• Engage with the Characterization pillars (Channel, Size, Potential, Territorial Profile, Digital Autonomy) and facilitate their expansion across multiple countries.

• Analyze the P&L comprehensively and convert it into decision variables, costs, and objective functions.

• Document assumptions and confirm results with business and finance stakeholders.

• Create analyses, features, and models on Databricks while collaborating with Data Engineers and Analytics Engineers.

• Advocate for best practices in modeling, reproducibility, and documentation throughout the team.

⛳️ Requirements

• Proven background and experience in Operations Research / Optimization (including linear and integer programming, constrained optimization).

• Proficient in interpreting a P&L and translating it into variables, costs, and objective functions.

• Advanced proficiency in Python, particularly with optimization libraries (PuLP, Pyomo, OR-Tools, or similar).

• Strong foundation in statistics and modeling.

• Practical experience with Databricks.

• Skillful in translating business requirements into analytical solutions and effectively communicating complex findings to both technical and non-technical audiences.