Applied Scientist: Dynamic Pricing & Real-Time Optimization

Lyft; New York (NY); Hybrid; USD 140,800 - 176,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Mental health benefits

401(k) plan with company match

Discretionary paid time off

Subsidized commuter benefits

Monthly Lyft credits and complimentary Lyft Pink membership

Job summary

A leading rideshare company is looking for an Applied Scientist specializing in Machine Learning and Operations Research. You will create mathematical models for pricing and ETAs to enhance the user experience while collaborating with cross-functional teams. The ideal candidate will have advanced degrees in relevant fields and experience in algorithms within technology settings. This position supports a hybrid work model, requiring in-office work three days a week.

Qualifications

• Strong understanding of machine learning methodologies and experience with optimization models.
• Proficiency in production coding environments, particularly with Python.
• Experience in collaborating with Data Scientists and Engineers to implement algorithms.

Responsibilities

• Develop mathematical models and algorithms for pricing and ETAs implementation.
• Conduct data analysis to propose ML and Optimization solutions.
• Collaborate with cross-functional teams to frame problems mathematically.

Skills

Machine Learning

Operations Research

Python

Statistical Analysis

Data Analysis

Education

M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, or Computer Science

Job description

A leading rideshare company is looking for an Applied Scientist specializing in Machine Learning and Operations Research. You will create mathematical models for pricing and ETAs to enhance the user experience while collaborating with cross-functional teams. The ideal candidate will have advanced degrees in relevant fields and experience in algorithms within technology settings. This position supports a hybrid work model, requiring in-office work three days a week.