Data Scientist - Algorithms, Mapping

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.

As a Data Scientist on the Mapping team, you will collaborate with our world class team of scientists, engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to ...

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. The Mapping team serves models and systems that determine the most efficient routes, fastest travel est...

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
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.