Data Scientist

• Translate complex business challenges into well-defined technical problems solvable with data, statistics, and machine learning. • Collaborate with product managers, engineers, and business stakeholders to build and scale data science solutions that power driver allocations, surge pricing and driver incentives. • Own the full ML lifecycle—from ideation and research to model development, pipeline implementation, deployment, experimentation, and driving measurable business outcomes. • Improve the efficiency of our dynamic driver incentives using techniques from machine learning, causal inference, optimization and simulation • Design and interpret experiments to measure model impact, working with analysts and product teams to ensure rigorous evaluation and clear success metrics. • Monitor and evaluate model performance, identifying areas for improvement and proposing solutions • Communicate insights, trade-offs, and technical decisions effectively to cross-functional stakeholders, and operate with a high degree of autonomy in ambiguous problem spaces. • Bachelor’s or Master’s degree in Computer Science, Statistics, Machine Learning, or a related quantitative field • Solid understanding of statistics and machine learning fundamentals, with coursework or projects demonstrating practical application. • Proficiency in Python and SQL, and familiarity with data analysis or modeling libraries. • Strong analytical thinking and problem-solving skills, with the ability to reason from data and communicate findings clearly. • A willingness to learn fast, take initiative, and work collaboratively in a cross-functional team. • Curiosity, humility, and a drive to apply data science to real-world problems at scale.