Staff Data Scientist I – Matching

As a Staff Data Scientist I – Matching, you will own the end-to-end matching and dispatch architecture for the company's Food and Groceries verticals. You will design and implement real-time assignment systems that optimize cost, SLA compliance, and marketplace efficiency at scale. This role sits at the core of the marketplace engine solving complex, multi-objective optimization problems under uncertainty. You will build systems that dynamically match orders to captains, optimize batching and pooling decisions, and continuously re-optimize as new information arrives. You will operate as a senior technical IC, leading architecture decisions, mentoring other data scientists, and setting optimization standards across the domain.

Location
Dubai, United Arab Emirates

What You'll Do

• 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.
• 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.
• 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.
• 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.

What You'll Need

• 6–8+ years of experience in Applied Machine Learning, Optimization, or Data Science.
• Advanced degree in Computer Science, Engineering, Operations Research, Mathematics, or a related quantitative field.
• Strong expertise in:
  • Optimization and assignment algorithms
  • Graph modeling and min-cost flow problems
  • Multi-objective optimization
  • Dynamic and online decision systems
• Hands-on experience with OR-Tools or custom optimization solvers.
• Proficiency in Python, SQL, Spark, and distributed data systems.
• Experience building real-time or near-real-time decision systems.
• Strong understanding of experimentation and performance evaluation in marketplace systems.
• Excellent communication skills with the ability to explain algorithmic trade-offs in business terms.

What we’ll provide you
We offer colleagues the opportunity to drive impact in the region while they learn and grow. As a full-time colleague, you will be able to:

• Work and learn from great minds by joining a community of inspiring colleagues.
• Put your passion to work in a purposeful organisation dedicated to creating impact in a region with a lot of untapped potential.
• Explore new opportunities to learn and grow every day.
• Work 4 days a week in office & 1 day from home, and remotely from any country in the world for 30 days a year with unlimited vacation days per year. (If you are in an individual contributor role in tech, you will have 2 office days a week and 3 to work from home.)
• Access to healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.