Senior Applied Scientist

About the role

Lead the design and implementation of optimization architectures, including problem formulation and solver selection. Develop and own mathematical frameworks for generating optimized allocation plans, integrating complex business constraints. Architect multi-objective optimization solutions to balance key metrics such as in-stock rates, inventory turns, and operational costs. Provide expert guidance to the optimization team on problem decomposition and strategic solution approaches across different regions. Collaborate with customer supply chain planning teams to define constraints and translate business rules into technical specifications. Apply advanced analytical techniques to solve real-world problems in a dynamic environment.

Requirements

• Strong foundation in Operations Research (MS or PhD preferred), with expertise in optimization techniques.
• Proven experience with optimization solvers such as Gurobi, CPLEX, or similar industry-standard tools.
• Ability to effectively translate complex business constraints into precise mathematical formulations.
• Proficiency in Python for advanced numerical computing and data analysis.
• Demonstrated experience in leading or mentoring other applied scientists.
• Deep domain knowledge in retail supply chain or inventory optimization.

Benefits

• Opportunity to work on challenging and impactful projects with significant real-world application.
• A collaborative and innovative environment that encourages continuous learning and professional growth.
• Be part of a team driving technological advancements and shaping the future of optimization.