About the company
Data Science is at the heart of Lyft's products and decision-making. The Driver Incentives Science team owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency.
Responsibilities
- 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 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
Requirements
- Advanced degree (MS or PhD, PhD preferred) in Operations Research, Applied Math, Computer Science, Statistics, Engineering, or related area; or equivalent work experience
- 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 designing, running, and analyzing A/B tests
Conditions
- Hybrid schedule: in-office at least 3 days per week (Mondays, Wednesdays, Thursdays)
- Expected base pay range for Toronto area: CAD $108,000 - CAD $135,000
- Extended health and dental coverage, life insurance, disability benefits
- Mental health benefits, family building benefits, child care and pet benefits
- RRSP plan with company match
- Flexible paid time off policy
- 18 weeks of paid parental leave