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Home/Jobs/Staff Data Scientist I - Matching
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Careem

Staff Data Scientist I - Matching

šŸ‡¦šŸ‡Ŗ Dubai, UAEšŸ¢ On-site
Data ScienceMachine LearningOptimizationAIPythonAlgorithm DevelopmentReal-time SystemsScalable Architecture
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Careem is building the Everything App for the greater Middle East — making it easy to move around, order food and groceries, manage payments, and more. Our purpose is simple: to simplify and improve people’s lives and build an awesome organisation that inspires.
Since 2012, Careem has enabled earnings for over 2.5 million Captains, simplified the lives of more than 70 million customers, and built a platform where the region’s best talent and entrepreneurs thrive. We operate in 70+ cities across 10 countries, from Morocco to Pakistan.

We’re now entering our next chapter — one powered by AI. We’re looking for AI talent: curious problem-solvers who know how to apply AI to build tools, automate workflows, and create real impact. Whether it’s streamlining operations, enhancing customer experience, or reimagining internal systems — we want people who can make Careem work smarter and move faster.

About the Role

As a Staff Data Scientist I – Matching, you will own the end-to-end matching and dispatch architecture for Careem’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.

What You'll Do

1. 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.

2. 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.

3. 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.

4. 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.

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 Careem 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.

Requirements

  • •End-to-end ownership of matching and dispatch systems for Food & Groceries.
  • •Design and implement scalable assignment frameworks.
  • •Formulate and implement multi-objective optimization models.
  • •Develop and deploy Min-cost flow and assignment models.
  • •Develop and deploy Graph-based optimization frameworks.
  • •Develop and deploy custom solvers.
  • •Operate as a senior technical IC.
  • •Mentor other data scientists.

Nice to Have

  • •Experience with OR-Tools.

Responsibilities

  • •Design and implement real-time assignment systems.
  • •Optimize cost, SLA compliance, and marketplace efficiency at scale.
  • •Build systems that dynamically match orders to captains.
  • •Optimize batching and pooling decisions.
  • •Continuously re-optimize as new information arrives.
  • •Set optimization standards across the domain.

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