Drimva

Lyft

Senior Data Scientist, Algorithms, Lyft Biz

$148K–$185K

New York, NY +2 · Senior · Full-time · Posted Jul 6, 2026

Location
New York, NY
New York, New York, United States
San Francisco, California, United States
Experience
5+ years of hands-on experience developing, deploying, and maintaining production machine-learning models and optimization systems.
Education
Master’s or PhD in Machine Learning, Computer Science, Statistics, Optimization, or a related quantitative field (or equivalent applied experience).

About the job

Leads data science and algorithm development across Lyft Business products, building and deploying machine-learning solutions, experimentation, and analytics to improve growth, efficiency, and enterprise outcomes.

What you'll do

  • Lead end-to-end machine-learning, AI, and causal-inference initiatives, from problem formulation through deployment and monitoring.
  • Develop experimentation and evaluation frameworks, and optimize production ML systems for performance, reliability, cost, and latency.
  • Guide cross-functional work, set algorithmic direction, and mentor other scientists.

What they ask for

  • 5+ years of hands-on experience developing, deploying, and maintaining production machine-learning models and optimization systems.
  • Master’s or PhD in a related quantitative field, or equivalent applied experience.
  • Deep knowledge of supervised and unsupervised learning, ranking/decisioning systems, probabilistic modeling, and causal inference.
  • Strong proficiency in Python, modern ML frameworks, and distributed data systems; experience with production ML architectures and rigorous experimentation.

Pay

$148,000 - $185,000 USD base salary

Tools

Python, PyTorch, TensorFlow, scikit-learn, Spark, Snowflake, Databricks

AI focus

Leads machine-learning and AI initiatives, including production ML models, optimization, experimentation, and algorithmic methods such as reinforcement learning and graph-based techniques.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 5, 2026 (UTC)