Data Scientist, Mapping & Routing Algorithms

Socket.dev; Toronto; Hybrid; CAD 108,000 - 135,000; Full time

Job summary

Lyft in Toronto is seeking a Data Scientist on the Mapping team to leverage geospatial and mobility data to improve routing and travel time estimates for riders and drivers.

You will own the full lifecycle of ML solutions, partner with Engineering to scale systems, run experiments, and drive data‑driven product decisions.

This hybrid role requires collaboration with cross‑functional partners, strong communication, and a passion for solving complex geospatial problems.

Qualifications

• Advanced degree in a quantitative field or equivalent experience.
• 3+ years in data science or ML roles with production models.
• Experience with ML in production balancing accuracy, compute, and maintainability.
• Strong communication and cross‑functional collaboration.
• Familiarity with PyTorch, TensorFlow, Ray, or Spark.

Responsibilities

• Own the complete lifecycle of algorithmic solutions from problem formulation to deployment.
• Lead deep dives into data to uncover product opportunities.
• Partner with Engineering to scale production‑grade ML systems and pipelines.
• Design, implement, and analyze experiments to drive data‑driven decisions.
• Drive ML research with modern techniques to unlock new product capabilities.
• Establish metrics to measure health of products and rider/driver experience.
• Translate business challenges into concrete algorithmic solutions with Product, Engineering, Operations, and Science teams.

Skills

PyTorch

TensorFlow

Ray

Spark

Communication

Education

Advanced degree in quantitative field

Job description

Lyft in Toronto is seeking a Data Scientist on the Mapping team to leverage geospatial and mobility data to improve routing and travel time estimates for riders and drivers.

You will own the full lifecycle of ML solutions, partner with Engineering to scale systems, run experiments, and drive data‑driven product decisions.

This hybrid role requires collaboration with cross‑functional partners, strong communication, and a passion for solving complex geospatial problems.