Staff Applied Scientist

Job Summary

Leading research and development efforts, the full-time remote Staff Applied Scientist will focus on advancing AI/ML models for inventory control, tackling complex challenges related to perishability and consumer demand.

Key responsibilities

• Set technical direction for core replenishment R&D, aligning modeling roadmaps with business strategy
• Model complex inventory-related problems and implement solutions for multi-stage inventory optimization
• Drive changes from research to production, ensuring rigorous testing and scalability of code

Required qualifications

• MS or PhD in Operations Research, Industrial Engineering, Computer Science, Electrical Engineering, or a related quantitative field
• 8+ years of industry experience for MS holders; 4+ years for PhD holders
• Experience in large-scale decision-making systems under uncertainty
• Prior work in inventory optimization, supply chain management, or stochastic optimization is a plus
• Ability to deliver high-quality software implementations using the Python data stack