Staff Data Scientist I - Matching

Overview

• Matching & Dispatch Architecture Ownership

• Design and own the end-to-end matching and dispatch systems for Food & Groceries.
• Architect scalable assignment frameworks incorporating:
• Static and dynamic assignment
• Online matching under uncertainty
• Batch and pooling optimization
• Continuous re-optimization with dynamic events
• Establish robust optimization standards and best practices across the organization.

• Multi-Objective Optimization & Algorithm Development

• Formulate and implement multi-objective optimization models balancing:
• Cost minimization
• SLA compliance
• Marketplace efficiency
• Develop and deploy:
• Min-cost flow and assignment models
• Graph-based optimization frameworks
• Custom solvers and OR-Tools based solutions
• Incorporate stochastic elements and uncertainty-aware decision-making into assignment policies.
• Continuously refine matching quality under high-scale marketplace conditions.

• Real-Time Systems & Production Delivery

• Build production-grade real-time matching systems using Python, Spark, and Trino.
• Design scalable pipelines capable of handling large-scale, high-throughput marketplace events.
• Collaborate with Engineering and Platform teams to ensure reliable model serving and system performance.
• Lead performance monitoring, diagnostics, and system optimization.

• Experimentation & Impact Measurement

• Define evaluation metrics aligned with marketplace and operational objectives.
• Design and run controlled experiments to quantify matching improvements.
• Analyze system trade-offs and communicate clear, data-driven recommendations to Product and Operations stakeholders.
• Ensure decisions translate into measurable improvements in efficiency and SLA performance.