Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms
Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting
Write production model code; collaborate with Software Engineers to implement algorithms in production
Perform exploratory data analysis to gain a deeper understanding of the marketplace and its users
Communicate findings and facilitate launch decisions with technical and non-technical stakeholders
Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies
Advanced degree (MS or PhD, PhD preferred) in a quantitative field like Operations Research, Applied Math, Computer Science, Statistics, Engineering, or a related area; or equivalent work experience
Passion for solving unstructured and non-standard mathematical problems, with 2+ years of hands-on experience in optimization (preferred), causal inference, or machine learning
End-to-end experience with data, including querying, aggregation, analysis, and visualization
Proficiency with Python
Strong ability to collaborate and communicate with others in a team setting
Experience seeking out and adopting new methods and techniques
Experience designing, running, and analyzing A/B tests to validate hypotheses and inform decision-making