Staff Data Scientist I - ETA

Overview

• 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 at scale.
• This 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.
• 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.
• 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.
• 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 productionize models using Spark, Trino, Python, and distributed frameworks.
• Lead model lifecycle management, retraining strategies, and performance tracking in live environments.
• 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.
• 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.