Staff Data Scientist I

Responsibilities

• Apply AI to drive measurable business impact in the Mobility space, mainly Marketplace and Captains (drivers) user experience. Topics include: multi-objective cost function for supply-demand matching, multi-modal transport matching, ETA optimizations, peak pricing for supply and demand shaping, pooling for mobility of people, batching for mobility of things, Captain entity embedding and 360 features understanding, Captain behavior engagement through sequential learning.
• Deeply understand the business and user needs and design appropriate metrics to improve how products meet those needs
• Create and improve team processes and set a technical team vision and strategy
• Mentor junior data scientists
• Perform analysis on raw event data in modern data warehouse systems
• Take ambiguous business and technical problems to an appropriate solution
• Use expertise in causal inference, machine learning, complex systems modeling, behavioral decision theory etc. to shape the future of Careem
• Develop relation and collaborate with your Uber’s counterparts on ML applications

Qualifications

• 6+ years experience in applied AI and operationalization of AI at scale
• Experience in applied Deep Learning and Reinforcement Learning
• Expertise in machine learning frameworks (like Keras, TensorFlow, or PyTorch) and libraries (like scikit-learn)
• Deep knowledge of traditional ML concepts such as GMMs, SVMs, trees, and boosting as well as more recent deep learning fundamentals
• Advanced degree in a quantitative discipline such as Physics, Statistics, Mathematics, Engineering or Computer Science.
• Strong problem solving and coding skills.
• Excellent oral and written communication skills.
• Proficiency and demonstrated experience in at least 2 of the following: Python, SQL, Spark, Hive.
• Experience with upskilling teammates with new ML technologies and infrastructures
• Experience with large-scale distributed databases (e.g., Spark)
• Experience with data orchestration tools (e.g., Airflow) and streaming systems
• Experience with online controlled experimentation
• Previous publication experience in conferences such as CVPR, ICCV, NeurIPS, and ICLR will be great to have.