Careem - Staff Data Scientist I - Matching
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Requirements
• Must-haves: • Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or a related technical field • 6+ years of experience working with machine learning program management, analytics in any form- ideally in tech, e-commerce, or service excellence organizations. • Solid Python skills, especially with libraries like pandas, NumPy, and scikit-learn • A strong grasp of ML fundamentals like classification, regression, cross-validation, and evaluation metrics • Familiarity with at least one ML framework such as TensorFlow, PyTorch, or XGBoost • Advanced analytical capability: proficiency in SQL, Excel, Power BI / Tableau, or other BI tools. • Proven track record of translating data insights into business strategy and measurable impact. • Advanced analytical capability: proficiency in SQL, Excel, Power BI / Tableau, or other BI tools - ability to translate complex data into simple narratives. • Familiarity with CRM and Care platforms (Zendesk, Salesforce, or equivalent) and workflow automation tools. • Nice-to-haves: • Exposure to deep learning techniques in call center • Experience working with large datasets using Spark, Hive, and cloud tools • Familiarity with model deployment and monitoring workflows (Airflow, MLflow, etc.) • Interest in solving real operational challenges for customers, captains and partners • A GitHub profile or project portfolio that shows what you’ve built. • What you’ll get • What you’ll get • A chance to work on AI problems, data-analytics at regional scale that improve lives and drive real business outcomes • A smart, motivated team that values learning and practical impact • Flexibility to work remotely, with strong support for collaboration and ownership • A front-row seat to how AI is transforming mobility, delivery, and digital services in emerging markets • 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. 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 • 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.
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