Applied Scientist- Pricing, Dynamic Pricing & Offer Selection

Lyft Lyft · Consumer · San Francisco, CA · Pricing

Lyft is seeking an Applied Scientist to develop and launch ML and optimization models for dynamic pricing and offer selection, productionalizing pipelines that scale to millions of calls per day. The role involves leveraging expertise in ML and Operations Research to solve real-world marketplace problems, balancing complexity and efficiency to create reliable solutions.

What you'd actually do

  1. Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
  2. Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries.
  3. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.
  4. Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems
  5. Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes

Skills

Required

  • Python
  • Machine Learning
  • Operations Research
  • Statistics
  • Computer Science
  • building and evaluating optimization or machine learning models
  • production coding environment

Nice to have

  • custom methods and tooling beyond off-the-shelf libraries

What the JD emphasized

  • production quality code
  • production-grade ML and Optimization models
  • scale to millions of calls per day
  • building impactful machine learning models

Other signals

  • develop mathematical models
  • launch algorithms
  • build ML and optimization models
  • productionalize pipelines
  • scale to millions of calls per day
  • real-world problems across optimization, prediction, machine learning, and inference