Careem - Staff Data Scientist I - ETA
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT
Requirements
• 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 • 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. • 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.
Responsibilities
• 1. 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. • 2. 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. • 3. 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 productionize models using Spark, Trino, Python, and distributed frameworks. • Lead model lifecycle management, retraining strategies, and performance tracking in live environments. • 4. 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. • 5. 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.
No credit card. Takes 10 seconds.