Data Scientist, Algorithms - Lyft Ads

Lyft

New York, NY, United States
Base: $128,000 - $160,000; bonus/equity: not speci...
On-site
Production-grade machine learning models
Large-scale datasets
Real-time systems
Lyft Ads is building the world’s largest transportation media network to help brands reach riders during key moments of their journey

Job Summary

  • Lyft Ads is building the world’s largest transportation media network to help brands reach riders during key moments of their journey.
  • Responsibilities include designing, developing, and deploying production-grade machine learning models for core Lyft Ads capabilities, owning the end-to-end lifecycle of modeling projects, and collaborating with Ads Engineering to integrate models into real-time systems.
  • Benefits include comprehensive medical, dental, and vision insurance, mental health benefits, family building benefits, 401(k) plan, discretionary paid time off, and 18 weeks of paid parental leave.

Matching Summary

Lyft Ads is building the world’s largest transportation media network to help brands reach riders during key moments of their journey.

Salary

Base: $128,000 - $160,000; Bonus/Equity: Not specified; Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled, Mental health benefits, Family building benefits, Child care and pet benefits, 401(k) plan, discretionary paid time off, 18 weeks of paid parental leave, Subsidized commuter benefits, Lyft Pink

Skills & Requirements

Must-have

  • production-grade machine learning models
  • large-scale datasets
  • real-time systems
  • Python
  • PyTorch, TensorFlow, JAX, or scikit-learn
  • Spark, Snowflake, Presto, Databricks
  • ranking and relevance models
  • optimization or pacing algorithms
  • predictive models for CTR, CVR, or user response
  • causal or experimentation-based measurement methods
  • online/offline evaluation techniques
  • A/B testing methodologies
  • bias correction and counterfactual estimation
  • rigorous algorithmic solutions

Nice-to-have

  • applied machine learning intuition
  • hands-on modeling experience
  • clean, efficient production code
  • collaboration with Engineering, Product, Data Science, and Sales
  • innovation and staying current with ML advances

Key Requirements

  • Master's, or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative fields; or equivalent applied industry experience
  • 3–5 years of hands-on ML/applied science experience
  • Experience working with large-scale datasets and distributed data tools
  • Understanding of online/offline evaluation techniques
  • Ability to solve ambiguous problems
  • Strong communication skills
  • Demonstrated ownership of modeling work
  • Curiosity, initiative, and a track record of delivering measurable improvements

Work Rights

Not specified

Tailored Resume

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