Data Scientist - ETA

About the Company

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.

As a Staff Data Scientist I – ETA, you will own the end‑to‑end ETA prediction systems for Careem’s Food and Groceries verticals. This is a highly technical Individual Contributor role with full domain ownership across architecture, modeling strategy, experimentation, production deployment, and operational excellence.

You will define the long‑term vision for ETA systems in high‑load, latency‑sensitive marketplace environments. You will design and implement multi‑stage stochastic pipelines that model preparation time, assignment delay, pickup time, travel time, batching, and pooling effects delivering reliable, calibrated predictions s role requires deep expertise in time‑series forecasting, deep learning, and operations research combined with strong production experience in distributed and real‑time systems.

You will collaborate closely with Product, Engineering, Marketplace, and Operations leaders, ensuring ETA becomes a core competitive advantage in Careem’s Everything App.

• ETA Vision & Architecture Ownership
• Define and own the long‑term technical vision for ETA systems across Food and Groceries.
• Architect scalable, multi‑stage pipelines.
• Design probabilistic and stochastic modeling approaches with uncertainty calibration and reliability guarantees.
• Establish modeling standards and best practices for ETA across the organization.
• Advanced Modeling & Algorithm Development
• Develop and deploy production‑grade ML systems leveraging:
  • Deep learning architectures
  • Time‑series forecasting
  • Graph‑based and routing‑aware models
  • Operations research techniques
• Build models robust to marketplace volatility and supply‑demand shifts.
• Optimize for both point accuracy and distributional correctness (confidence intervals, tail control).
• Continuously improve system performance under high traffic and low‑latency constraints.
• Production Systems & Real‑Time Inference
• Design and deploy scalable real‑time inference pipelines.
• Ensure model reliability, monitoring, alerting, and graceful degradation under load.
• Collaborate with Data Platform and ML Ops teams to product ionize models using Spark, Trino, Python, and distributed frameworks.
• Lead model lifecycle management, retraining strategies, and performance tracking in live environments.
• Experimentation & Marketplace Impact
• Define clear evaluation frameworks aligned with business metrics (conversion, cancellations, fulfillment efficiency, customer trust).
• Design and run controlled experiments to measure ETA improvements and marketplace impact.
• Drive measurable improvements in operational efficiency and user experience through data‑driven insights.
• Technical Leadership & Cross‑Team Influence
• Lead cross‑team architectural discussions.
• Conduct design reviews and raise the technical bar for modeling quality and system robustness.
• Mentor senior data scientists and engineers in advanced ML and modeling techniques.
• Contribute to Careem’s applied AI community through technical talks, documentation, and research initiatives.

• 8+ years of experience in Applied Machine Learning or Data Science, with significant experience building large‑scale production systems.
• Advanced degree in Computer Science, Statistics, Engineering, Operations Research, or a related…