Staff Data Scientist I - ETA

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.
  

• 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 quantitative field.
• Proven expertise in:
• Time-series forecasting
• Deep learning
• Stochastic modeling
• Operations research and optimization
• Strong experience building and deploying high-load, low-latency ML systems.
• Hands-on proficiency in Python, Spark and ML frameworks.
• Experience with real-time inference systems and model monitoring in production.
• Strong understanding of experimentation, A/B testing, and causal inference.
• Demonstrated ability to drive architectural decisions across teams.
• Excellent communication skills and ability to translate complex modeling trade-offs into business impact.
  

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.