About the company
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.
Responsibilities
- Own the complete lifecycle of algorithmic solutions from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration
- Prioritize and lead deep dives into our data to uncover new product and business opportunities
- Partner closely with Engineering to build and scale production-grade ML systems, real-time inference services, batch pipelines, and feature stores
- Design, implement, and analyze different types of experiments, and facilitate and foster data-driven and informed decision making and prioritization
- Drive scientific excellence by introducing modern techniques in ML, optimization, reinforcement learning, or graph-based methods to unlock new product capabilities
- Establish metrics that measure the health of our products, as well as rider and driver experience
- Translate complex business challenges into concrete algorithmic solutions in close collaboration with Product, Engineering, Operations, and Science teams
Requirements
- Advanced degree in a quantitative field such as statistics, physics, economics, operations research, neuroscience, or engineering, or relevant work experience
- 3+ years hands-on experience in a data science or machine learning role working with production machine learning models and optimization systems
- Passion for solving unstructured and non-standard mathematical problems
- Experience independently driving multi-project algorithmic scopes and navigating technical ambiguity from ideation to delivery
- Experience with machine learning models in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments
- Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners
- Working knowledge of modern machine learning frameworks and distributed computing systems, including PyTorch, TensorFlow, Ray, Spark, etc.
Conditions
- Extended health and dental coverage options, along with life insurance and disability benefits
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- Access to a Lyft funded Health Care Savings Account
- RRSP plan with company match to help save for your future
- Flexible paid time off policy
- 18 weeks of paid time off for new parents
- Subsidized commuter benefits and Lyft ride credits