The opportunity
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
What you'll do
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.
What they're looking for
- 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.
