Applied Scientist: Real-Time Pricing & OR

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

Benefits offered by this job

Medical insurance

Mental health benefits

Family building benefits

Child care support

401(k) with company match

Paid time off

Parental leave

Commuter benefits

Lyft credits

Lyft Pink membership

Job summary

Lyft is seeking an Applied Scientist specializing in Machine Learning and Operations Research to develop models powering dynamic pricing and ETA decisions. You will productionalize pipelines handling millions of calls daily and collaborate with Product Managers, Engineers, and Analysts.

The role emphasizes solving complex business problems with scalable ML and optimization, balancing efficiency and accuracy in a fast-paced environment.

Qualifications

• MS/PhD in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative field.
• 2+ years of algorithms experience in a tech setting.
• Proficiency with Python and production coding.
• Ability to translate complex problems into reliable ML/Optimization solutions.

Responsibilities

• Frame problems mathematically within business context.
• Write production-quality code for ML and optimization models.
• Perform data analysis and build proof-of-concepts for ML/Optimization solutions.
• Evaluate ML systems against business goals and deploy in live systems.
• Establish metrics to monitor health and impacts of products.
• Collaborate with cross-functional teams across Pricing.

Skills

Python

Machine Learning

Optimization

Data analysis

Communication

Education

MS/PhD in ML/OR/Statistics/CS

Tools

Production coding environments

Job description

Lyft is seeking an Applied Scientist specializing in Machine Learning and Operations Research to develop models powering dynamic pricing and ETA decisions. You will productionalize pipelines handling millions of calls daily and collaborate with Product Managers, Engineers, and Analysts.

The role emphasizes solving complex business problems with scalable ML and optimization, balancing efficiency and accuracy in a fast-paced environment.