Pricing Forecasting Engineer (Hybrid)

engineeringjobs.net, Inc.; Toronto (OH); Hybrid; USD 76,000 - 95,000; Full time

Benefits offered by this job

Health coverage

Mental health benefits

Family building benefits

Commuter benefits

Lyft Health Savings Account

RRSP match

Flexible PTO

Parental leave (18 weeks)

Job summary

Lyft’s Planned Pricing team seeks engineers to design and operate pricing, forecasting, and decision systems that balance rider and driver needs. You will work on large-scale distributed data pipelines, experimentation, and forecasting accuracy to improve the Lyft experience for millions.

The role emphasizes collaboration across product, science, and engineering. The position is in-office on a hybrid schedule in Toronto, requiring at least 3 days per week in the office, with up to 4 weeks remote

Qualifications

• BS/MS in Computer Engineering, CS, or related field.
• 1–3 years software engineering experience.
• Experience in backend systems and distributed/concurrent design.
• Strong written and verbal communication skills.

Responsibilities

• Design, develop, deploy, monitor, operate and maintain systems and infrastructure.
• Collaborate with engineers and product to drive projects from inception to launch.
• Write well-crafted, tested, readable and maintainable code.
• Participate in code reviews to ensure code quality.
• Design and own the way pricing data is consumed, stored, and shared across Lyft.
• Share knowledge via brown bags and tech talks.
• Utilize Python, Go, AWS to deliver scalable solutions.

Skills

Python

Go

OO programming

Communication

Education

BS/MS or equivalent in Computer Engineering/CS

Tools

AWS

Job description

Lyft’s Planned Pricing team seeks engineers to design and operate pricing, forecasting, and decision systems that balance rider and driver needs. You will work on large-scale distributed data pipelines, experimentation, and forecasting accuracy to improve the Lyft experience for millions.

The role emphasizes collaboration across product, science, and engineering. The position is in-office on a hybrid schedule in Toronto, requiring at least 3 days per week in the office, with up to 4 weeks remote